publications.bib

%%%%%%%%%%%%
%%  2026  %%
%%%%%%%%%%%%

@article{acmhealth-2026,
  author = {Queiroz Neto, Dilermando and Carlos, Anderson and Anjos,
  Andr{\'{e}} and Berton, Lilian},
  keywords = {Fairness, Foundation Models, World Health},
  month = jan,
  title = {Fair Foundation Models for Medical Image Analysis:
  Challenges and Perspectives},
  journal = {ACM Transactions on Computing for Healthcare},
  year = {2026},
  doi = {10.1145/3793542},
  abstract = {Ensuring equitable Artificial Intelligence (AI) in
    healthcare demands systems that make unbiased decisions across all
    demographic groups, bridging technical innovation with ethical
    principles. Foundation Models (FMs), trained on vast datasets
    through self-supervised learning, enable efficient adaptation
    across medical imaging tasks while reducing dependency on labeled
    data. These models demonstrate potential for enhancing fairness,
    though significant challenges remain in achieving consistent
    performance across demographic groups. Our review indicates that
    effective bias mitigation in FMs requires systematic interventions
    throughout all stages of development. While previous approaches
    focused primarily on model-level bias mitigation, our analysis
    reveals that fairness in FMs requires integrated interventions
    throughout the development pipeline, from data documentation to
    deployment protocols. This comprehensive framework advances current
    knowledge by demonstrating how systematic bias mitigation, combined
    with policy engagement, can effectively address both technical and
    institutional barriers to equitable AI in healthcare. The
    development of equitable FMs represents a critical step toward
    democratizing advanced healthcare technologies, particularly for
    underserved populations and regions with limited medical
  infrastructure and computational resources.},
}

@article{scirep-2026,
  author = {Amiot, Victor and Pulvirenti, Roberto and
    Jimenez-del-Toro, Oscar and Ott, Muriel and Bogaciu,
    Teodora-Elena and Banerjee, Shalini and Amstutz, Christoph and
    Odobez, Jean-Marc and Chiquet, Christophe and Guex-Crosier, Yan
    and Bergin, Ciara and Meloni, Ilenia and Anjos, Andr{\'{e}} and
  Hoogewoud, Florence and Tomasoni, Mattia},
  keywords = {Clinical translation, deep learning, disease grading,
  fluorescein angiography, inter-grader agreement, Uveitis, vasculitis},
  month = may,
  title = {UveAI: clinic-ready scoring of retinal inflammation in
  uveitis on widefield fluorescein angiography using AI},
  journal = {Scientific reports},
  year = {2026},
  url = {https://www.nature.com/articles/s41598-026-46069-w},
  doi = {10.1038/s41598-026-46069-w},
  abstract = {Retinal inflammation is a key determinant of visual
    prognosis in uveitis, yet its assessment on fluorescein
    angiography remains subjective, labor-intensive, and
    insufficiently scalable for clinical trials or large cohort
    studies. Fluorescein angiography is the gold standard for
    assessing retinal inflammation. However, its scoring remains
    challenging, as the process is complex and time-consuming,
    limiting routine use in clinical trials and patient care. We
    present UveAI, a modular deep learning framework that grades all
    major retinal inflammatory signs in fluorescein angiography
    across posterior pole and periphery to generate an ASUWOG-aligned
    inflammation score. Trained on 3,220 FA images from 644 eyes (369
    patients), UveAI integrates six transformer models detecting
    macular edema, optic disc hyperfluorescence, and vascular and
    capillary leakage in the posterior pole and periphery. On an
    independent test set, UveAI showed high concordance with an
    expert grader for total score (R = 0.96) and strong performance
    for individual signs (mean AUC = 0.952). Grad-CAM maps confirmed
    clinically relevant focus, supporting automated, standardised FA
  scoring in uveitis.}
}

@inproceedings{isbi-2026,
  author = {Pulvirenti, Roberto and Jimenez-del-Toro, Oscar and
    Tomasoni, Mattia and
  Hoogewoud, Florence and Anjos, Andr{\'{e}}},
  title = {When Specialization Helps (and Hurts): Cross-Modality
  Transfer in Ophthalmic Imaging with Foundation Models},
  booktitle = {2026 IEEE 23rd International Symposium on Biomedical Imaging},
  year = {2026},
  url = {https://www.idiap.ch/paper/retinal-fm-specialization/},
  doi = {10.1109/ISBI61048.2026.11515636},
  abstract = {Large publicly available datasets for specialized
    medical imaging are rare, limiting model development and
    motivating knowledge transfer from related, data-rich modalities.
    We explore this in ophthalmology by investigating whether retinal
    foundation models (FMs) pretrained on Color Fundus Photographs
    (CFP) transfer more effectively to other ophthalmic modalities,
    specifically Fluorescein Angiography (FA) and Indocyanine Green
    Angiography (ICGA), than nonspecialist FMs trained on natural
    images. In particular, we examine how the Self-Supervised
    Learning (SSL) strategy and model size influence this transfer.
    Using the public AngioReport dataset, six FMs were fine-tuned on
    three angiography tasks and thoroughly evaluated. Attention-based
    analyses, performed both quantitatively and qualitatively,
    further contextualized the results. Our experiments show that
    cross-modality transfer in retinal FMs is critically dependent on
    the SSL method applied during the pretraining phase: while DINOv2
    and Token-Reconstruction objectives preserve diverse
    representations that generalize well across modalities, MAE
    pretraining leads to overspecialization, a narrowing of
    representations that limits transferability to other retinal
  imaging domains.}
}

%%%%%%%%%%%%
%%  2025  %%
%%%%%%%%%%%%

@article{melba-2025,
  author = {{\"{O}}zbulak, G{\"{o}}khan and Jimenez-del-Toro, Oscar
  and Fatoretto, Ma{\'{\i}}ra and Berton, Lilian and Anjos, Andr{\'{e}}},
  keywords = {machine learning, Medical Image Analysis,
    multi-objective optimization, Multidimensional Fairness Evaluation,
  Utility-Fairness Trade-off},
  month = dec,
  title = {A Multi-Objective Evaluation Framework for Analyzing
  Utility-Fairness Trade-Offs in Machine Learning Systems},
  journal = {The Journal of Machine Learning for Biomedical Imaging},
  volume = {3},
  year = {2025},
  pages = {938-957},
  doi = {10.59275/j.melba.2025-ab9a},
  abstract = {The evaluation of fairness models in Machine Learning
    involves complex challenges, such as defining appropriate metrics,
    balancing trade-offs between utility and fairness, and there are
    still gaps in this stage. This work presents a novel
    multi-objective evaluation framework that enables the analysis of
    utility-fairness trade-offs in Machine Learning systems. The
    framework was developed using criteria from Multi-Objective
    Optimization that collect comprehensive information regarding this
    complex evaluation task. The assessment of multiple Machine
    Learning systems is summarized, both quantitatively and
    qualitatively, in a straightforward manner through a radar chart
    and a measurement table encompassing various aspects such as
    convergence, system capacity, and diversity. The framework’s
    compact representation of performance facilitates the comparative
    analysis of different Machine Learning strategies for
    decision-makers, in real-world applications, with single or
    multiple fairness requirements. In particular, this study focuses
    on the medical imaging domain, where fairness considerations are
    crucial due to the potential impact of biased diagnostic systems on
    patient outcomes. The proposed framework enables a systematic
    evaluation of multiple fairness constraints, helping to identify
    and mitigate disparities among demographic groups while maintaining
    diagnostic performance. The framework is model-agnostic and
    flexible to be adapted to any kind of Machine Learning systems,
    that is, black- or white-box, any kind and quantity of evaluation
    metrics, including multidimensional fairness criteria. The
    functionality and effectiveness of the proposed framework are shown
    with different simulations, and an empirical study conducted on
    three real-world medical imaging datasets with various Machine
    Learning systems. Our evaluation framework is publicly available at
  https://pypi.org/project/fairical.},
}

@article{cbm-2025,
  author = {Amiot, Victor and Jimenez-del-Toro, Oscar and
    Guex-Croisier, Yan and Ott, Muriel and Bogaciu, Teodora-Elena and
    Banerjee, Shalini and Howell, Jeremy and Amstutz, Christoph and
    Chiquet, Christophe and Bergin, Ciara and Meloni, Ilenia and
  Tomasoni, Mattia and Hoogewoud, Florence and Anjos, Andr{\'{e}}},
  keywords = {deep learning, fluorescein angiography, inter-grader
  agreement, Optic disease grading, transformers, Uveitis, vasculitis},
  month = jul,
  title = {Automatic transformer-based grading of multiple retinal
  inflammatory signs in uveitis on fluorescein angiography},
  journal = {Computers in Biology and Medicine},
  volume = {193},
  number = {110327},
  year = {2025},
  issn = {0010-4825},
  url = {https://github.com/JulesGoninRIO/uveitis_transformers},
  doi = {10.1016/j.compbiomed.2025.110327},
  abstract = {Grading fluorescein angiography (FA) for uveitis is
    complex, often leading to the oversight of retinal inflammation
    in clinical studies. This study aims to develop an automated
    method for grading retinal inflammation.
    Methods. Patients from Jules-Gonin Eye Hospital with active or
    resolved uveitis who underwent FA between 2018 and 2021 were
    included. FAs were acquired using a standardized protocol,
    anonymized, and annotated following the Angiography Scoring for
    Uveitis Working Group criteria, for four inflammatory signs of
    the posterior pole. Intergrader agreement was assessed by four
    independent graders. Four deep learning transformer models were
    developed, and performance was evaluated using the Ordinal
    Classification Index, accuracy, F1 scores, and Kappa scores.
    Saliency analysis was employed to visualize model predictions.
    Findings. A total of 543 patients (1042 eyes, 40987 images) were
    included in the study. The models closely matched expert graders
    in detecting vascular leakage (F1-score =
    0{\textperiodcentered}87, 1-OCI = 0{\textperiodcentered}89),
    capillary leakage (F1-score = 0{\textperiodcentered}86, 1-OCI =
    0{\textperiodcentered}89), macular edema (F1-score =
    0{\textperiodcentered}82, 1-OCI = 0{\textperiodcentered}86), and
    optic disc hyperfluorescence (F1-score =
    0{\textperiodcentered}72, 1-OCI = 0{\textperiodcentered}85).
    Saliency analysis confirmed that the models focused on relevant
    retinal structures. The mean intergrader agreement across all
    inflammatory signs was F1-score = 0{\textperiodcentered}79 and
    1-OCI = 0{\textperiodcentered}83.
    Interpretation. We developed a vision transformer-based model for
    the automatic grading of retinal inflammation in uveitis, utilizing
    the largest dataset of FAs in uveitis to date. This approach
    provides significant clinical benefits for the evaluation of
    uveitis and paves the way for future advancements, including the
    identification of novel biomarkers through the integration of
  clinical data and other modalities.}
}

@article{asoc-2025,
  author = {Fatoreto, Maira and {\"{O}}zbulak, G{\"{o}}khan and
  Berton, Lilian and Anjos, Andr{\'{e}}},
  month = sep,
  title = {Optimizing Fairness and Utility in Healthcare Machine
  Learning Models},
  journal = {Applied Soft Computing},
  volume = {181},
  number = {113426},
  year = {2025},
  doi  = {10.1016/j.asoc.2025.113426},
  abstract = {Demographic fairness or equity is a crucial aspect of
    machine learning models, particularly in critical domains such as
    healthcare, where errors can have severe consequences. A fair model
    avoids making distinctions between groups with different sensitive
    or protected attributes. Although several metrics are available to
    measure fairness and ensure equity between groups, proposed
    solutions must uphold fairness without compromising the utility of
    these models. Optimization problems that incorporate both fairness
    and utility information can help find the best machine learning
    model. Mathematical programming emerges as a valuable tool in this
    context. One approach is to use optimization functions with
    constraints, imposing a maximum difference between groups. In this
    sense, considering multiple constraints that encompass various
    sensitive attributes present in the dataset when adjusting the
    models is essential to ensure intersectional fairness, minimize
    hidden biases, and promote equitable decisions in diverse contexts.
    In this work, we propose to constrain the minimization of the loss
    function with multiple fairness-related metrics, ensuring that
    fairness metrics do not exceed a maximum limit concerning the
    impartiality of the decision boundary. We use metrics derived from
    Pareto fronts, a method used in multi-objective optimization,
    adapting it for single-objective optimization and incorporating
    fairness characteristics into the constraints. The points observed
    in this graph use different fairness thresholds. We compare our
    proposed model with existing literature and demonstrate the
    convergence of our model to logistic regression with simulated
    data. Furthermore, we apply this strategy to health-related
    datasets and other domains present in most fairness and
    optimization articles. As a result, we found that, using the
    proposed metrics, our model performs better, even with imbalanced
  data concerning sensitive attributes and smaller datasets.}
}

@inproceedings{ijcb-2025,
  author = {Vitek, Matej and Toma{\v s}evi{\'{c}}, Darian and Das,
    Abhijit and Nathan, Sabari and {\"{O}}zbulak, G{\"{o}}khan and
    Tataroğlu {\"{O}}zbulak, G{\"{o}}zde Ayşe and Calbimonte, Jean-Paul
    and Anjos, Andr{\'{e}} and Hemant Bhatt, Hariohm and Dhirendra
    Premani, Dhruv and Chaudhari, Jay and Wang, Caiyong and Jiang, Jian
    and Zhang, Chi and Zhang, Qi and Iyappan Ganapathi, Iyyakutti and
    Sadaf Ali, Syed and Velayudan, Divya and Assefa, Maregu and Werghi,
    Naoufel and A Daniels, Zachary and John, Leeon and Vyas, Ritesh and
    Nourmohammadi Khiarak, Jalil and Akbari Saeed, Taher and Nasehi,
    Mahsa and Kianfar, Ali and Pashazadeh Panahi, Mobina and Sharma,
    Geetanjali and Raj Panth, Pushp and Ramachandra, Raghavendra and
  Nigam, Aditya and Pal, Umapada and Pedrini, Helio and Struc, Vitomir},
  title = {Privacy-enhancing Sclera Segmentation Benchmarking
  Competition: SSBC 2025},
  booktitle = {International Joint Conference on Biometrics},
  year = {2025},
  publisher = {IEEE},
  doi = {10.48550/arXiv.2508.10737},
  abstract = {This paper presents a summary of the 2025 Sclera
    Segmentation Benchmarking Competition (SSBC), which focused on the
    development of privacy-preserving sclera-segmentation models
    trained using synthetically generated ocular images. The goal of
    the competition was to evaluate how well models trained on
    synthetic data perform in comparison to those trained on real-world
    datasets. The competition featured two tracks: one relying solely
    on synthetic data for model development, and one combining/mixing
    synthetic with (a limited amount of) real-world data. A total of
    nine research groups submitted diverse segmentation models,
    employing a variety of architectural designs, including
    transformer-based solutions, lightweight models, and segmentation
    networks guided by generative frameworks. Experiments were
    conducted across three evaluation datasets containing both
    synthetic and real-world images, collected under diverse
    conditions. Results show that models trained entirely on synthetic
    data can achieve competitive performance, particularly when
    dedicated training strategies are employed, as evidenced by the top
    performing models that achieved scores of over in the synthetic
    data track. Moreover, performance gains in the mixed track were
    often driven more by methodological choices rather than by the
    inclusion of real data, highlighting the promise of synthetic data
    for privacy-aware biometric development. The code and data for the
  competition is available at: https://github.com/dariant/SSBC_2025.}
}

@inproceedings{aime-2025,
  author = {Geissbuhler, Damien and Bornet, Alban and Marques,
    Catarina and Anjos, Andr{\'{e}} and Pereira, S{\'{o}}nia and
  Teodoro, Douglas},
  keywords = {Hospital-Acquired Infections, Multidrug Resistance
    Prediction, Sparse Clinical Data Integration, Spatiotemporal
  Modeling, Temporal Graph Neural Networks},
  month = 6,
  title = {STM-GNN: Space-Time-and-Memory Graph Neural Networks for
  Predicting Multi-Drug Resistance Risks in Dynamic Patient Networks},
  booktitle = {International Conference on Artificial Intelligence
  in Medicine},
  year = {2025},
  location = {Pavia, Italy},
  isbn = {978-3-031-95838-0},
  doi = {10.1007/978-3-031-95838-0_16},
  abstract = {Hospital-acquired infections (HAIs), particularly those
    caused by multidrug-resistant (MDR) bacteria, pose significant
    risks to vulnerable patients. Accurate predictive models are
    important for assessing infection dynamics and informing infection
    prediction and control (IPC) programmes. Graph-based methods,
    including graph neural networks (GNNs), offer a powerful approach
    to model complex relationships between patients and environments
    but often struggle with data sparsity, irregularity, and
    heterogeneity. We propose the space-time-and-memory (STM)-GNN, a
    temporal GNN enhanced with recurrent connectivity designed to
    capture spatiotemporal infection dynamics. STM-GNN effectively
    integrates sparse, heterogeneous data combining network information
    from patient-environment interactions and internal memory from
    historical colonization and contact patterns. Using a unique IPC
    dataset containing clinical and environmental colonization
    information collected from a long-term healthcare unit, we show
    that STM-GNN effectively addresses the challenges of limited and
    irregular data in an MDR prediction task. Our model reaches 0.84
    AUROC, and achieves the most balanced performance overall compared
  to classic machine learning algorithms, as well as temporal GNN approaches.}
}

%%%%%%%%%%%%
%%  2024  %%
%%%%%%%%%%%%

@misc{ssrn-2024,
  title = {Automatic Transformer-Based Grading of Multiple Retinal
  Inflammatory Signs on Fluorescein Angiography},
  url = {https://papers.ssrn.com/abstract=4960069},
  doi = {10.2139/ssrn.4960069},
  abstract = {Background: Grading fluorescein angiography ({FA}) in
    the context of uveitis is complex, often leading to the oversight
    of retinal inflammation in clinical studies. This study aims to
  develop an automated method for grading retinal inflammation.},
  number = {4960069},
  author = {Amiot, Victor and Jimenez-del-Toro, Oscar and
    Guex-Croisier, Yan and Ott, Muriel and Bogaciu, Teodora-Elena and
    Banerjee, Shalini and Howell, Jeremy and Amstutz, Christoph and
    Chiquet, Christophe and Bergin, Ciara and Meloni, Ilenia and
  Tomasoni, Mattia and Hoogewoud, Florence and Anjos, André},
  year = {2024},
  month = 9,
  day = 24,
  keywords = {capillaropathy, Deep Learning, disease grading,
    fluorescein angiography, inter-grader agreement, macular edema,
    optic disc hyperfluorescence, ordinal classification index,
    papillitis, retinal inflammation, transformers, Uveitis, vascular
  leakage, vasculitis},
}

@inproceedings{miccai-2024,
  author = {Queiroz Neto, Dilermando and Anjos, Andr{\'{e}} and
  Berton, Lilian},
  keywords = {Fairness, Foundation Model, Medical Image},
  month = 10,
  title = {Using Backbone Foundation Model for Evaluating Fairness in
  Chest Radiography Without Demographic Data},
  booktitle = {Proceedings of the International Conference on Medical
  Image Computing and Computer Assisted Intervention (MICCAI)},
  year = {2024},
  doi = {10.1007/978-3-031-72787-0_11},
  abstract = {Ensuring consistent performance across diverse
    populations and incorporating fairness into machine learning models
    are crucial for advancing medical image diagnostics and promoting
    equitable healthcare. However, many databases do not provide
    protected attributes or contain unbalanced representations of
    demographic groups, complicating the evaluation of model
    performance across different demographics and the application of
    bias mitigation techniques that rely on these attributes. This
    study aims to investigate the effectiveness of using the backbone
    of Foundation Models as an embedding extractor for creating groups
    that represent protected attributes, such as gender and age. We
    propose utilizing these groups in different stages of bias
    mitigation, including pre-processing, in-processing, and
    evaluation. Using databases in and out-of-distribution scenarios,
    it is possible to identify that the method can create groups that
    represent gender in both databases and reduce in 4.44\% the
    difference between the gender attribute in-distribution and 6.16\%
    in out-of-distribution. However, the model lacks robustness in
    handling age attributes, underscoring the need for more
    fundamentally fair and robust Foundation models. These findings
    suggest a role in promoting fairness assessment in scenarios where
    we lack knowledge of attributes, contributing to the development of
  more equitable medical diagnostics.},
  pdf =
  {https://publications.idiap.ch/attachments/papers/2024/QueirozNeto_CVPR_2024.pdf}
}

@inproceedings{eccv-2024,
  author = {Queiroz Neto, Dilermando and Carlos, Anderson and
    Fatoretto, Ma{\'{\i}}ra and Nakayama, Luis Filipe and Anjos,
  Andr{\'{e}} and Berton, Lilian},
  projects = {FAIRMI},
  month = 10,
  title = {Does Data-Efficient Generalization Exacerbate Bias in
  Foundation Models?},
  booktitle = {Proceedings of the 18th European Conference on
  Computer Vision (ECCV)},
  year = {2024},
  doi = {10.48550/arXiv.2408.16154},
  abstract = {Foundation models have emerged as robust models with
    label efficiency in diverse domains. In medical imaging, these
    models contribute to the advancement of medical diagnoses due to
    the difficulty in obtaining labeled data. However, it is unclear
    whether using a large amount of unlabeled data, biased by the
    presence of sensitive attributes during pre-training, influences
    the fairness of the model. This research examines the bias in the
    Foundation model (RetFound) when it is applied to fine-tune the
    Brazilian Multilabel Ophthalmological Dataset (BRSET), which has a
    different population than the pre-training dataset. The model
    evaluation, in comparison with supervised learning, shows that the
    Foundation Model has the potential to reduce the gap between the
    maximum AUC and minimum AUC evaluations across gender and age
    groups. However, in a data-efficient generalization, the model
    increases the bias when the data amount decreases. These findings
    suggest that when deploying a Foundation Model in real-life
    scenarios with limited data, the possibility of fairness issues
  should be considered.},
  pdf =
  {https://publications.idiap.ch/attachments/papers/2024/QueirozNeto_ECCV_2024.pdf}
}

@inproceedings{euvip-2024-2,
  author = {Jimenez-del-Toro, Oscar and Aberle, Christoph and Schaer,
    Roger and Bach, Michael and Flouris, Kyriakos and Konukoglu, Ender
    and Stieltjes, Bram and Obmann, Markus M. and Anjos, Andr{\'{e}}
  and M{\"{u}}ller, Henning and Depeursinge, Adrien},
  month = 9,
  title = {Comparing Stability and Discriminatory Power of
    Hand-crafted Versus Deep Radiomics: A 3D-Printed Anthropomorphic
  Phantom Study},
  booktitle = {Proceedings of the 12th European Workshop on Visual
  Information Processing},
  year = {2024},
  doi = {10.1109/EUVIP61797.2024.10772813},
  abstract = {Radiomics have the ability to comprehensively quantify
    human tissue characteristics in medical imaging studies. However,
    standard radiomic features are highly unstable due to their
    sensitivity to scanner and reconstruction settings. We present an
    evaluation framework for the extraction of 3D deep radiomics
    features using a pre-trained neural network on real computed
    tomography (CT) scans for tissue characterization. We compare both
    the stability and discriminative power of the proposed 3D deep
    learning radiomic features versus standard hand-crafted radiomic
    features using 8 image acquisition protocols with a 3D-printed
    anthropomorphic phantom containing 4 classes of liver lesions and
    normal tissue. Even when the deep learning model was trained on an
    external dataset and for a different tissue characterization task,
    the resulting generic deep radiomics are at least twice more stable
    on 8 CT parameter variations than any category of hand-crafted
    features. Moreover, the 3D deep radiomics were also discriminative
    for the tissue characterization between 4 classes of liver tissue
  and lesions, with an average discriminative power of 93.5\%.},
  pdf =
  {https://publications.idiap.ch/attachments/papers/2024/Jimenez-del-Toro_EUVIP2024_2024.pdf}
}

@inproceedings{euvip-2024-1,
  author = {G{\"{u}}ler, {\"{O}}zg{\"{u}}r and G{\"{u}}nther, Manuel
  and Anjos, Andr{\'{e}}},
  month = 9,
  title = {Refining Tuberculosis Detection in CXR Imaging: Addressing
  Bias in Deep Neural Networks via Interpretability},
  booktitle = {Proceedings of the 12th European Workshop on Visual
  Information Processing},
  year = {2024},
  doi = {10.1109/EUVIP61797.2024.10772829},
  abstract = {Automatic classification of active tuberculosis from
    chest X-ray images has the potential to save lives, especially in
    low- and mid-income countries where skilled human experts can be
    scarce. Given the lack of available labeled data to train such
    systems and the unbalanced nature of publicly available datasets,
    we argue that the reliability of deep learning models is limited,
    even if they can be shown to obtain perfect classification accuracy
    on the test data. One way of evaluating the reliability of such
    systems is to ensure that models use the same regions of input
    images for predictions as medical experts would. In this paper, we
    show that pre-training a deep neural network on a large-scale proxy
    task, as well as using mixed objective optimization network (MOON),
    a technique to balance different classes during pre-training and
    fine-tuning, can improve the alignment of decision foundations
    between models and experts, as compared to a model directly trained
    on the target dataset. At the same time, these approaches keep
    perfect classification accuracy according to the area under the
    receiver operating characteristic curve (AUROC) on the test set,
    and improve generalization on an independent, unseen dataset. For
  the purpose of reproducibility, our source code is made available online.},
  pdf =
  {https://publications.idiap.ch/attachments/papers/2024/Guler_EUVIP24_2024.pdf}
}

@article{mvr-2024,
  author = {Mautuit, Thibaud and Cunnac, Pierre and Truffer,
    Fr{\'{e}}d{\'{e}}ric and Anjos, Andr{\'{e}} and Dufrane, Rebecca
  and Ma{\^{\i}}tre, Gilbert and Geiser, Martial and Chiquet, Christophe},
  month = 1,
  title = {Absolute retinal blood flow in healthy eyes and in eyes
  with retinal vein occlusion},
  journal = {Microvascular Research},
  volume = {152},
  year = {2024},
  issn = {0026-2862},
  doi = {10.1016/j.mvr.2023.104648},
  abstract = {Purpose: To measure non-invasively retinal venous blood flow
    (RBF) in healthy subjects and patients with retinal venous
    occlusion (RVO).

    Methods: The prototype named AO-LDV (Adaptive Optics Laser Doppler
    Velocimeter), which combines a new absolute laser Doppler
    velocimeter with
    an adaptive optics fundus camera (rtx1, Imagine Eyes{\textregistered},
    Orsay, France), was studied for the measurement of absolute RBF as a
    function of retinal vessel diameters and simultaneous measurement of red
    blood cell velocity. RBF was measured in healthy subjects (n = 15) and
    patients with retinal venous occlusion (RVO, n = 6). We also
    evaluated two
    softwares for the measurement of retinal vessel diameters: software 1
    (automatic vessel detection, profile analysis) and software 2
    (based on the
      use of deep neural networks for semantic segmentation of
      vessels, using a
    M2u-Net architecture).

    Results: Software 2 provided a higher rate of automatic retinal vessel
    measurement (99.5 \% of 12,320 AO images) than software 1 (64.9 \%) and
    wider measurements (75.5 ± 15.7 μm vs 70.9 ± 19.8 μm, p < 0.001). For
    healthy subjects (n = 15), all the retinal veins in one eye
    were measured
    to obtain the total RBF. In healthy subjects, the total RBF
    was 37.8 ± 6.8
    μl/min. There was a significant linear correlation between
    retinal vessel
    diameter and maximal velocity (slope = 0.1016; p < 0.001; r2
    = 0.8597) and
    a significant power curve correlation between retinal vessel
    diameter and
    blood flow (3.63 × 10−5 × D2.54; p < 0.001; r2 = 0.7287). No significant
    relationship was found between total RBF and systolic and
    diastolic blood
    pressure, ocular perfusion pressure, heart rate, or hematocrit. For RVO
    patients (n = 6), a significant decrease in RBF was noted in
    occluded veins
    (3.51 ± 2.25 μl/min) compared with the contralateral healthy
    eye (11.07 ±
    4.53 μl/min). For occluded vessels, the slope between
    diameter and velocity
    was 0.0195 (p < 0.001; r2 = 0.6068) and the relation between
    diameter and
    flow was Q = 9.91 × 10−6 × D2.41 (p < 0.01; r2 = 0.2526).

    Conclusion: This AO-LDV prototype offers new opportunity to study
    RBF in humans
  and to evaluate treatment in retinal vein diseases.},
}

%%%%%%%%%%%%
%%  2023  %%
%%%%%%%%%%%%

@inproceedings{cbms-2023,
  author = {Amiot, Victor AND Jimenez-del-Toro, Oscar AND Eyraud,
    Pauline AND Guex-Crosier, Yan AND Bergin, Ciara AND Anjos, André
  AND Hoogewoud, Florence AND Tomasoni, Mattia},
  title = {Fully Automatic Grading of Retinal Vasculitis on
    Fluorescein Angiography Time-lapse from Real-world Data in
  Clinical Settings},
  booktitle={2023 IEEE 36th International Symposium on Computer-Based
  Medical Systems (CBMS)},
  year = {2023},
  month = 6,
  doi = {10.1109/CBMS58004.2023.00301},
  abstract = {The objective of this study is to showcase a pipeline
    able to perform fully automated grading of retinal inflammation
    based on a standardised, clinically-validated grading scale. The
    application of such scale has so far been hindered by the the
    amount of time required to (manually) apply it in clinical
    settings. Our dataset includes 3,205 fluorescein angiography images
    from 148 patients and 242 eyes from the uveitis department of Jules
    Gonin Eye Hospital. The data was automatically extracted from a
    medical device, in hospital settings. Images were graded by a
    medical expert. We focused specifically on one type of
    inflammation, namely retinal vasculitis. Our pipeline comprises
    both learning-based models (Pasa model with F1 score = 0.81, AUC =
    0.86), and an intensity-based approach to serve as a baseline (F1
    score = 0.57, AUC = 0.66). A recall of up to 0.833 computed in an
    independent test set is comparable to the scores obtained by
    available state-of-the-art approaches. Here we present the first
    fully automated pipeline for the grading of retinal vasculitis from
  raw medical images that is applicable to a real-world clinical data.},
}

@article{ijtld-2023,
  title = {The rise of artificial intelligence reading of chest
  X-rays for enhanced TB diagnosis and elimination},
  doi = {10.5588/ijtld.22.0687},
  abstract = {We provide an overview of the latest evidence on
    computer-aided detection (CAD) software for automated
    interpretation of chest radiographs (CXRs) for TB detection. CAD is
    a useful tool that can assist in rapid and consistent CXR
    interpretation for TB. CAD can achieve high sensitivity TB
    detection among people seeking care with symptoms of TB and in
    population-based screening, has accuracy on-par with human readers.
    However, implementation challenges remain. Due to diagnostic
    heterogeneity between settings and sub-populations, users need to
    select threshold scores rather than use pre-specified ones, but
    some sites may lack the resources and data to do so. Efficient
    standardisation is further complicated by frequent updates and new
    CAD versions, which also challenges implementation and comparison.
    CAD has not been validated for TB diagnosis in children and its
    accuracy for identifying non-TB abnormalities remains to be
    evaluated. A number of economic and political issues also remain to
    be addressed through regulation for CAD to avoid furthering health
    inequities. Although CAD-based CXR analysis has proven remarkably
    accurate for TB detection in adults, the above issues need to be
    addressed to ensure that the technology meets the needs of
  high-burden settings and vulnerable sub-populations.},
  journal = {INT J TUBERC LUNG DIS},
  volume = {27},
  journaltitle = {International Journal of Tuberculosis and Lung Diseases},
  author = {Geric, C. AND Qin, Z. Z. AND Denkinger, C. M. AND Kik, S.
    V. AND Marais, B. AND Anjos, André AND David, P.-M. AND Khan, F. A.
  AND Trajman, A.},
  year = {2023},
  month = 5,
  keywords = {computer-aided detection; chest radiology; pulmonary
  disease; tuberculosis; AI technology},
}

%%%%%%%%%%%%
%%  2022  %%
%%%%%%%%%%%%

@article{elsevier-csal-2022,
  title = {Towards lifelong human assisted speaker diarization},
  issn = {0885-2308},
  doi = {10.1016/j.csl.2022.101437},
  abstract = {This paper introduces the resources necessary to
    develop and evaluate human assisted lifelong learning speaker
    diarization systems. It describes the {ALLIES} corpus and
    associated protocols, especially designed for diarization of a
    collection audio recordings across time. This dataset is compared
    to existing corpora and the performances of three baseline systems,
    based on x-vectors, i-vectors and {VBxHMM}, are reported for
    reference. Those systems are then extended to include an active
    correction process that efficiently guides a human annotator to
    improve the automatically generated hypotheses. An open-source
    simulated human expert is provided to ensure reproducibility of the
    human assisted correction process and its fair evaluation. An
    exhaustive evaluation, of the human assisted correction shows the
    high potential of this approach. The {ALLIES} corpus, a baseline
    system including the active correction module and all evaluation
  tools are made freely available to the scientific community.},
  journal = {Computer Speech \& Language},
  journaltitle = {Computer Speech \& Language},
  author = {Shamsi, Meysam and Larcher, Anthony and Barrault, Loic
    and Meignier, Sylvain and Prokopalo, Yevheni and Tahon, Marie and
    Mehrish, Ambuj and Petitrenaud, Simon and Galibert, Olivier and
    Gaist, Samuel and Anjos, André and Marcel, Sebastien and
  Costa-jussà, Marta R.},
  year = {2022},
  month = 7,
  date = {2022-07-27},
  pdf = {https://www.idiap.ch/~aanjos/papers/elsevier-csal-2022.pdf},
  keywords = {Evaluation, Human assisted learning, Lifelong learning,
  Speaker diarization},
}

@inproceedings{union-2022,
  author = {Raposo, Geoffrey and Trajman, Anete and Anjos, Andr{\'{e}}},
  month = 11,
  title = {Pulmonary Tuberculosis Screening from Radiological Signs
  on Chest X-Ray Images Using Deep Models},
  booktitle = {Union World Conference on Lung Health},
  year = {2022},
  addendum = {(Issued from master thesis supervision)},
  date = {2022-11-01},
  organization = {The Union},
  abstract = {Background: The World Health Organization has recently
    recommended the use of computer-aided detection (CAD) systems for
    screening pulmonary tuberculosis (PT) in Chest X-Ray images.
    Previous CAD models are based on direct image to probability
    detection techniques - and do not generalize well (from training
    to validation databases). We propose a method that overcomes
    these limitations by using radiological signs as intermediary
    proxies for PT detection.

    Design/Methods: We developed a multi-class deep learning model,
    mapping images to 14 radiological signs such as cavities,
    infiltration, nodules, and fibrosis, using the National Institute
    of Health (NIH) CXR14 dataset, which contains 112,120 images.
    Using three public PTB datasets (Montgomery County - MC, Shenzen
    - CH, and Indian - IN), summing up 955 images, we developed a
    second model mapping F probabilities to PTB diagnosis (binary
    labels). We evaluated this approach for its generalization
    capabilities against direct models, learnt directly from PTB
    training data or by transfer learning via cross-folding and
    cross-database experiments. The area under the specificity vs.
    sensitivity curve (AUC) considering all folds was used to
    summarize the performance of each approach.

    Results: The AUC for intra-dataset tests baseline direct
    detection deep models achieved 0.95 (MC), 0.95 (CH) and 0.91
    (IN), with up to 35\% performance drop on a cross-dataset
    evaluation scenario. Our proposed approach achieved AUC of 0.97
    (MC), 0.90 (CH), and 0.93 (IN), with at most 11\% performance
    drop on a cross-dataset evaluation (Table/figures). In most
    tests, the difference was less than 5\%.

    Conclusions: A two-step CAD model based on radiological signs
    offers an adequate base for the development of PT screening systems
    and is more generalizable than a direct model. Unlike commercially
    available CADS, our model is completely reproducible and available
  open source at https://pypi.org/project/bob.med.tb/.}
}

@article{nsr-2022,
  title = {State-of-the-art retinal vessel segmentation with
  minimalistic models},
  volume = {12},
  rights = {2022 The Author(s)},
  issn = {2045-2322},
  url = {https://www.nature.com/articles/s41598-022-09675-y},
  pdf = {https://www.nature.com/articles/s41598-022-09675-y.pdf},
  doi = {10.1038/s41598-022-09675-y},
  abstract = {The segmentation of retinal vasculature from eye fundus
    images is a fundamental task in retinal image analysis. Over recent
    years, increasingly complex approaches based on sophisticated
    Convolutional Neural Network architectures have been pushing
    performance on well-established benchmark datasets. In this paper,
    we take a step back and analyze the real need of such complexity.
    We first compile and review the performance of 20 different
    techniques on some popular databases, and we demonstrate that a
    minimalistic version of a standard U-Net with several orders of
    magnitude less parameters, carefully trained and rigorously
    evaluated, closely approximates the performance of current best
    techniques. We then show that a cascaded extension (W-Net) reaches
    outstanding performance on several popular datasets, still using
    orders of magnitude less learnable weights than any previously
    published work. Furthermore, we provide the most comprehensive
    cross-dataset performance analysis to date, involving up to 10
    different databases. Our analysis demonstrates that the retinal
    vessel segmentation is far from solved when considering test images
    that differ substantially from the training data, and that this
    task represents an ideal scenario for the exploration of domain
    adaptation techniques. In this context, we experiment with a simple
    self-labeling strategy that enables moderate enhancement of
    cross-dataset performance, indicating that there is still much room
    for improvement in this area. Finally, we test our approach on
    Artery/Vein and vessel segmentation from {OCTA} imaging problems,
    where we again achieve results well-aligned with the
    state-of-the-art, at a fraction of the model complexity available
    in recent literature. Code to reproduce the results in this paper
  is released.},
  addendum = {(Issued from internship supervision)},
  pages = {6174},
  number = {1},
  journal = {Nature Scientific Reports},
  journaltitle = {Scientific Reports},
  shortjournal = {Sci Rep},
  author = {Galdran, Adrian and Anjos, André and Dolz, José and
  Chakor, Hadi and Lombaert, Hervé and Ayed, Ismail Ben},
  year = {2022},
  month = 4,
  date = {2022-04-13},
  langid = {english},
  note = {Number: 1
  Publisher: Nature Publishing Group},
  keywords = {Biomedical engineering, Computer science, Machine learning},
}

%%%%%%%%%%%%
%%  2021  %%
%%%%%%%%%%%%

@inproceedings{cbic-2021,
  title = {Development of a lung segmentation algorithm for analog
  imaged chest X-Ray: preliminary results},
  url = {https://sbic.org.br/eventos/cbic_2021/cbic2021-123/},
  pdf = {https://www.idiap.ch/~aanjos/papers/cbic-2021.pdf},
  doi = {10.21528/CBIC2021-123},
  shorttitle = {Development of a lung segmentation algorithm for
  analog imaged chest X-Ray},
  addendum = {(Issued from internship supervision)},
  abstract = {Analog X-Ray radiography is still used in many
    underdeveloped regions around the world.  To allow these
    populations to benefit from advances in automatic computer-aided
    detection (CAD) systems, X-Ray films must be digitized.
    Unfortunately, this procedure may introduce imaging artefacts,
    which may severely impair the performance of such systems.

    This work investigates the impact digitized images may cause to
    deep neural networks trained for lung (semantic) segmentation on
    digital x-ray samples. While three public datasets for lung
    segmentation evaluation exist for digital samples, none are
    available for digitized data.  To this end, a U-Net-style
    architecture was trained on publicly available data, and used to
    predict lung segmentation on a newly annotated set of digitized images.

    Using typical performance metrics such as the area under the
    precision-recall curve (AUPRC), our results show that the model
    is capable to identify lung regions at digital X-Rays with a high
    intra-dataset (AUPRC: 0.99), and cross-dataset (AUPRC: 0.99)
    efficiency on unseen test data.  When challenged against
    digitized data, the performance is substantially degraded (AUPRC: 0.90).

    Our analysis also suggests that typical performance markers,
    maximum F1 score and AUPRC, seems not to be informative to
    characterize segmentation problems in test images. For this goal
    pixels does not have independence due to natural connectivity of
    lungs in images, this implies that a lung pixel tends to be
    surrounded by other lung pixels.

    This work is reproducible.  Source code, evaluation protocols and
    baseline results are available at:
  https://pypi.org/project/bob.ip.binseg/.},
  eventtitle = {Congresso Brasileiro de Inteligência Computacional},
  pages = {1--8},
  booktitle = {Anais do 15. Congresso Brasileiro de Inteligência
  Computacional},
  year = {2021},
  month = 10,
  publisher = {{SBIC}},
  author = {Renzo, Matheus A. and Fernandez, Natália and Baceti,
  André A. and Moura Junior, Natanael Nunes and Anjos, André},
}

%%%%%%%%%%%%
%%  2020  %%
%%%%%%%%%%%%

@misc{arxiv-2020,
  title = {The Little W-Net That Could: State-of-the-Art Retinal
  Vessel Segmentation with Minimalistic Models},
  author = {Galdran, Adrian and Anjos, André and Dolz, José and
  Chakor, Hadi and Lombaert, Hervé and Ayed, Ismail Ben},
  year = {2020},
  month = 9,
  doi = {10.48550/arXiv.2009.01907},
  eprinttype = {arxiv},
  eprint        = {2009.01907},
  archivePrefix = {arXiv},
  primaryClass  = {cs.CV},
  journaltitle = {{arXiv}:2009.01907 [cs, eess] (submitted to Nature
  Scientific Reports)},
  url           = {https://arxiv.org/abs/2009.01907},
  pdf           = {https://arxiv.org/pdf/2009.01907},
  abstract = {The segmentation of the retinal vasculature from eye
    fundus images represents one of the most fundamental tasks in
    retinal image analysis. Over recent years, increasingly complex
    approaches based on sophisticated Convolutional Neural Network
    architectures have been slowly pushing performance on
    well-established benchmark datasets. In this paper, we take a step
    back and analyze the real need of such complexity. Specifically, we
    demonstrate that a minimalistic version of a standard UNet with
    several orders of magnitude less parameters, carefully trained and
    rigorously evaluated, closely approximates the performance of
    current best techniques. In addition, we propose a simple
    extension, dubbed W-Net, which reaches outstanding performance on
    several popular datasets, still using orders of magnitude less
    learnable weights than any previously published approach.
    Furthermore, we provide the most comprehensive cross-dataset
    performance analysis to date, involving up to 10 different
    databases. Our analysis demonstrates that the retinal vessel
    segmentation problem is far from solved when considering test
    images that differ substantially from the training data, and that
    this task represents an ideal scenario for the exploration of
    domain adaptation techniques. In this context, we experiment with a
    simple self-labeling strategy that allows us to moderately enhance
    cross-dataset performance, indicating that there is still much room
    for improvement in this area. Finally, we also test our approach on
    the Artery/Vein segmentation problem, where we again achieve
    results well-aligned with the state-of-the-art, at a fraction of
    the model complexity in recent literature. All the code to
  reproduce the results in this paper is released.},
}

@article{compbiomed-2020,
  title = {Competitive neural layer-based method to identify people
  with high risk for diabetic foot},
  volume = {120},
  url = {https://www.sciencedirect.com/science/article/pii/S0010482520301244},
  pdf = {https://www.idiap.ch/~aanjos/papers/compbiomed-2020.pdf},
  doi = {10.1016/j.compbiomed.2020.103744},
  abstract = {Background and objective: To automatically identify
    patients with diabetes mellitus (DM) who have high risk of
    developing diabetic foot, via an unsupervised machine learning
    technique.  Methods: We collected a new database containing 54
    known risk factors from 250 patients diagnosed with diabetes
    mellitus. The database also contained a separate validation cohort
    composed of 73 subjects, where the perceived risk was annotated by
    expert nurses. A competitive neuron layer-based method was used to
    automatically split training data into two risk groups.  Results:
    We found that one of the groups was composed of patients with
    higher risk of developing diabetic foot. The dominant variables
    that described group membership via our method agreed with the
    findings from other studies, and indicated a greater risk for
    developing such a condition. Our method was validated on the
    available test data, reaching 71\% sensitivity, 100\% specificity,
    and 90\% accuracy.  Conclusions Unsupervised learning may be
    deployed to screen patients with diabetes mellitus, pointing out
    high-risk individuals who require priority follow-up in the
    prevention of diabetic foot with very high accuracy. The proposed
    method is automatic and does not require clinical examinations to
    perform risk assessment, being solely based on the information of a
    questionnaire answered by patients. Our study found that
    discriminant variables for predicting risk group membership are
  highly correlated with expert opinion.},
  journal = {Computers in Biology and Medicine},
  author = {Ferreira, Ana Cl\'audia Barbosa Hon\'orio and Ferreira,
    Danton Diego and Oliveira, Henrique Ceretta and Resende, Igor
  Carvalho de and Anjos, Andr\'e and Lopes, Maria Helena Baena de Moraes},
  month = 5,
  year = {2020},
  keywords = {Artificial neural network, Diabetes mellitus, Diabetic foot},
}

%%%%%%%%%%%%
%%  2019  %%
%%%%%%%%%%%%

@misc{arxiv-2019,
  title         = {On the Evaluation and Real-World Usage Scenarios
  of Deep Vessel Segmentation for Retinography},
  author        = {Tim Laibacher and Andr\'e Anjos},
  addendum = {(Issued from intership supervision)},
  year          = {2019},
  month         = 9,
  eprint        = {1909.03856},
  archivePrefix = {arXiv},
  primaryClass  = {cs.CV},
  doi           = {10.48550/arXiv.1909.03856},
  url           = {https://arxiv.org/abs/1909.03856},
  pdf           = {https://arxiv.org/pdf/1909.03856},
  journaltitle = {{arXiv}:1909.03856 [cs] (submitted to IEEE
  International Symposium on Biomedical Imaging 2021)},
  abstract = {We identify and address three research gaps in the
    field of vessel segmentation for retinography.  The first focuses
    on the task of inference on high-resolution fundus images for which
    only a limited set of ground-truth data is publicly available.
    Notably, we highlight that simple rescaling and padding or cropping
    of lower resolution datasets is surprisingly effective.  We further
    explore the effectiveness of semi-supervised learning for better
    domain adaptation in this context.  Our results show competitive
    performance on a set of common public retina datasets, using a
    small and light-weight neural network.  For HRF, the only very
    high-resolution dataset currently available, we reach comparable,
    if not superior, state-of-the-art performance by solely relying on
    training images from lower-resolution datasets.  The second topic
    we address concerns the lack of standardisation in evaluation
    metrics.  We investigate the variability of the F1-score on the
    existing datasets and report results for recently published
    architectures.  Our evaluation show that most reported results are
    actually comparable to each other in performance.  Finally, we
    address the issue of reproducibility, by open-sourcing the complete
  framework used to produce results shown here.},
}

@patent{3dfv-patent-2019,
  author = {Sonna Momo, Lambert and Cerqueira Torres, Luciano and
    Marcel, S\'ebastien and Anjos, Andr\'e and Liebling, Michael and
    Shajkofci, Adrian and Amoos, Serge and Woeffray, Alain and Sierro,
  Alexandre and Roduit, Pierre and Ferrez, Pierre and Bonvin, Lucas},
  title = {Method and Device for Biometric Vascular Recognition
  and/or Identification},
  year = {2019},
  month = 8,
  day = 8,
  number = {WO/2019/150254},
  type = {Patent},
  filing_num = {PCT/IB2019/050708},
  yearfiled = {2019},
  monthfiled = 1,
  dayfiled = 29,
  pat_refs = {P\&TS SA (AG, LTD.); Av. J.-J. Rousseau 4 P.O. Box 2848
  2001 Neuchâtel, CH},
  abstract = {The invention concerns a method and a biometric
    acquisition device for biometric vascular recognition and/or
    identification. The method comprising a step of capturing a
    plurality of veins images (116, 117, 118) of supposed subcutaneous
    veins (21) of a same inspecting portion (20) of a presented entity
    (2) from various converging orientations (113, 114, 115). The
    method further comprises a step of determine if said entity is a
    spoof based on estimated likelihood that said supposed subcutaneous
    veins within said plurality of veins images (116, 117, 118) are
  likely projections of solid veins (120).},
  url = {https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2019150254}
}

@article{tifs-2019-2,
  author = {George, Anjith and Mostaani, Zohreh and Geissenbuhler,
    David and Nikisins, Olegs and Anjos, Andr{\'{e}} and Marcel,
  S{\'{e}}bastien},
  title = {Biometric Face Presentation Attack Detection with
  Multi-Channel Convolutional Neural Network},
  journal = {IEEE Transactions on Information Forensics and Security},
  month = 5,
  year = {2019},
  doi = {10.1109/TIFS.2019.2916652},
  pdf = {https://www.idiap.ch/~aanjos/papers/tifs-2019-2.pdf},
  abstract = {Face recognition is a mainstream biometric
    authentication method. However, vulnerability to presentation
    attacks (a.k.a spoofing) limits its usability in unsupervised
    applications. Even though there are many methods available for
    tackling presentation attacks (PA), most of them fail to detect
    sophisticated attacks such as silicone masks.
    As the quality of presentation attack instruments improves over
    time, achieving reliable PA detection with visual spectra alone
    remains very challenging. We argue that analysis in multiple
    channels might help to address this issue.  In this context, we
    propose a multi-channel Convolutional Neural Network based
    approach for presentation attack detection (PAD).
    We also introduce the new Wide Multi-Channel presentation Attack
    (WMCA) database for face PAD which contains a wide variety of 2D
    and 3D presentation attacks for both impersonation and obfuscation
    attacks. Data from different channels such as color, depth,
    near-infrared and thermal are available to advance the research in
    face PAD. The proposed method was compared with feature-based
    approaches and found to outperform the baselines achieving an ACER
    of 0.3\% on the introduced dataset. The database and the software
  to reproduce the results are made available publicly.},
}

@incollection{hopad-2019,
  title = {Recent Advances in Face Presentation Attack Detection},
  author = {Bhattacharjee, Sushil and Mohammadi, Amir and Anjos,
  Andr{\'{e}} and Marcel, S{\'{e}}bastien},
  editor = "Marcel, S{\'{e}}bastien AND Nixon, Mark AND Fierrez,
  Julian AND Evans, Nicholas",
  edition = "2nd edition (in press)",
  booktitle = "Handbook of Biometric Anti-Spoofing",
  publisher = "Springer-Verlag",
  year = "2019",
  month = 1,
  pages = "207--228",
  isbn = "ISBN 978-3-319-92627-8",
  doi = "10.1007/978-3-319-92627-8_10",
  abstract = "The undeniable convenience of face-recognition (FR)
  based biomet- rics has made it an attractive tool for access
  control in various applications, from immigration-control to remote
  banking. Widespread adoption of face biometrics, however, depends
  on the how secure such systems are perceived to be. One particular
  vulnerability of FR systems comes from presentation attacks (PA),
  where a subject A attempts to impersonate another subject B, by
  presenting, for example, a photograph of B to the biometric sensor
  (i.e., the camera). PAs are the most likely forms of attacks on
  face biometric systems, as the camera is the only component of the
  biometric system that is exposed to the outside world. Robust
  presentation attack detection (PAD) methods are necessary to
  construct secure FR based access control systems. The first edition
  of the Handbook of Biometric Anti-spoofing included two chapters on
  face-PAD. In this chapter we present the significant advances in
  face-PAD research since the publication of the first edition of
  this book. In addition to PAD methods designed to work with color
  images, we also discuss advances in face-PAD methods using other
  imaging modalities, namely, near-infrared (NIR) and thermal
  imaging. This chapter also presents a number of recently published
  datasets for face-PAD experiments.",
}

@incollection{hopad-2019-2,
  title = "Evaluation Methodologies for Biometric Presentation Attack
  Detection",
  author = {Chingovska, Ivana and Mohammadi, Amir and Anjos,
  Andr{\'{e}} and Marcel, S{\'{e}}bastien},
  editor = "Marcel, S{\'{e}}bastien AND Nixon, Mark AND Fierrez,
  Julian AND Evans, Nicholas",
  addendum = {(Issued from Ph.D co-supervision)},
  edition = "2nd edition (in press)",
  booktitle = "Handbook of Biometric Anti-Spoofing",
  publisher = "Springer-Verlag",
  year = "2019",
  month = 1,
  pages = "457--480",
  isbn = "ISBN 978-3-319-92627-8",
  doi = "10.1007/978-3-319-92627-8_20",
  abstract = "Presentation attack detection (PAD, also known as
  anti-spoofing) systems, regardless of the technique, biometric mode
  or degree of independence of external equipment, are most commonly
  treated as binary classification systems.  The two classes that
  they differentiate are bona-fide and presentation attack samples.
  From this perspective, their evaluation is equivalent to the
  established evaluation standards for the binary classification
  systems.  However, PAD systems are designed to operate in
  conjunction with recognition systems and as such can affect their
  performance. From the point of view of a recognition system, the
  presentation attacks are a separate class that they need to be
  detected and rejected. As the problem of presentation attack
  detection grows to this pseudo-ternary status, the evaluation
  methodologies for the recognition systems need to be revised and
  updated. Consequentially, the database requirements for
  presentation attack databases become more specific.  The focus of
  this chapter is the task of biometric verification and its scope is
  three-fold: firstly, it gives the definition of the presentation
  attack detection problem from the two perspectives. Secondly, it
  states the database requirements for a fair and unbiased
  evaluation. Finally, it gives an overview of the existing
  evaluation techniques for presentation attacks detection systems
  and verification systems under presentation attacks.",
}

@incollection{hopad-2019-3,
  title = "An Introduction to Vein Presentation Attacks and Detection",
  author = "Anjos, Andr{\'{e}} and Tome, Pedro and Marcel, S{\'{e}}bastien",
  editor = "Marcel, S{\'{e}}bastien AND Nixon, Mark AND Fierrez,
  Julian AND Evans, Nicholas",
  edition = "2nd edition (in press)",
  booktitle = "Handbook of Biometric Anti-Spoofing",
  publisher = "Springer-Verlag",
  year = "2019",
  month = 1,
  pages = "419--438",
  isbn = "ISBN 978-3-319-92627-8",
  doi = "10.1007/978-3-319-92627-8_18",
  abstract = "The domain of presentation attacks (PA), including
  vulnerability studies and detection (PAD) remains very much
  unexplored by available scientific literature in biometric vein
  recognition. Contrary to other modalities that use visual spectral
  sensors for capturing biometric samples, vein biometrics is
  typically implemented with near-infrared imaging. The use of
  invisible light spectra challenges the cre- ation PA instruments,
  but does not render it impossible. In this chapter, we provide an
  overview of current landscape for PA manufacturing in possible
  attack vectors for vein recognition, describe existing public
  databases and baseline techniques to counter such attacks. The
  reader will also find material to reproduce experiments and
  findings for fingervein recognition systems. We provide this
  material with the hope it will be extended to other vein
  recognition systems and improved in time.",
}

@article{tifs-2019,
  author = {de Freitas Pereira, Tiago and Anjos, André and Marcel, Sébastien},
  month = 12,
  title = {Heterogeneous Face Recognition Using Domain Specific Units},
  journal = {IEEE Transactions on Information Forensics and Security},
  year = {2019},
  addendum = {(Issued from Ph.D co-supervision)},
  doi = {10.1109/TIFS.2018.2885284},
  url = "https://publications.idiap.ch/index.php/publications/show/3963",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tifs-2018.pdf",
  abstract = {The task of Heterogeneous Face Recognition consists in
    matching face images that are sensed in different domains, such as
    sketches to photographs (visual spectra images), thermal images to
    photographs or near-infrared images to photographs. In this work we
    suggest that high level features of Deep Convolutional Neural
    Networks trained on visual spectra images are potentially domain
    independent and can be used to encode faces sensed in different
    image domains. A generic framework for Heterogeneous Face
    Recognition is proposed by adapting Deep Convolutional Neural
    Networks low level features in, so called, “Domain Specific Units”.
    The adaptation using Domain Specific Units allow the learning of
    shallow feature detectors specific for each new image domain.
    Furthermore, it handles its transformation to a generic face space
    shared between all image domains. Experiments carried out with four
    different face databases covering three different image domains
    show substantial improvements, in terms of recognition rate,
    surpassing the state-of-the-art for most of them. This work is made
    reproducible: all the source code, scores and trained models of
  this approach are made publicly available.},
}

%%%%%%%%%%%%
%%  2018  %%
%%%%%%%%%%%%

@inproceedings{iwbf-2018,
  author = "Nikisins, Olegs and Eglitis, Teodors and Anjos, André and
  Marcel, Sébastien",
  month = 6,
  title = "Fast cross-correlation based wrist vein recognition
  algorithm with rotation and  translation compensation",
  booktitle = "Sixth International Workshop on Biometrics and Forensics",
  year = "2018",
  url = "https://publications.idiap.ch/index.php/publications/show/3835",
  pdf = "https://www.idiap.ch/~aanjos/papers/iwbf-2018.pdf",
  doi= "10.1109/IWBF.2018.8401550",
  abstract = "Most of the research on vein biometrics addresses the
  problems of either palm or finger vein recognition with a
  considerably smaller emphasis on wrist vein modality. This paper
  paves the way to a better understanding of capabilities and
  challenges in the field of wrist vein verification. This is
  achieved by introducing and discussing a fully automatic
  cross-correlation based wrist vein verification technique.
  Overcoming the limitations of ordinary cross-correlation, the
  proposed system is capable of compensating for scale, translation
  and rotation between vein patterns in a computationally efficient
  way. Introduced comparison algorithm requires only two
  cross-correlation operations to compensate for both translation and
  rotation, moreover the well known property of log-polar
  transformation of Fourier magnitudes is not involved in any form.
  To emphasize the veins, a two-layer Hessian-based vein enhancement
  approach with adaptive brightness normalization is introduced,
  improving the connectivity and the stability of extracted vein
  patterns. The experiments on the publicly available PUT Vein wrist
  database give promising results with FNMR of 3.75\% for FMR of
  0.1\%. In addition we make this research reproducible providing the
  source code and instructions to replicate all findings in this work.",
}

@patent{beat-patent-2018,
  author = {Marcel Sébastien AND Anjos, André AND Abbet, Philip},
  title = {Method and internet-connected server for reviewing a
  computer-executable experiment},
  year = {2018},
  month = 5,
  day = 15,
  number = {US9973503B2},
  type = {Patent},
  location = {US},
  filing_num = {14/970,333},
  yearfiled = {2015},
  monthfiled = 12,
  dayfiled = 15,
  pat_refs = {P\&TS SA (AG, LTD.); Av. J.-J. Rousseau 4 P.O. Box 2848
  2001 Neuchâtel, CH},
  abstract = {An internet-connected server comprising a first module
    for authorizing a user to access the server for: setting up, on the
    server, a given configuration for conducting a computer-executable
    experiment, wherein the given configuration comprises at least an
    executable instruction and a parameter or input data; executing, on
    the server, the computer-executable experiment with the given
    configuration so to produce a numerical result; certifying, on the
    server, the numerical result so to produce a certified result; and
    generating, on the server, a certification identifier of the
    certified result. The internet-connected server further comprises a
    second module for authorizing a reviewer for: providing the server
    with the certification identifier; and requesting and/or accessing,
    on the server, the certified numerical result on the basis of the
  provided certification identifier.},
  url =
  {https://patft.uspto.gov/netacgi/nph-Parser?Sect2=PTO1&Sect2=HITOFF&p=1&u=/netahtml/PTO/search-bool.html&r=1&f=G&l=50&d=PALL&RefSrch=yes&Query=PN/9973503}
}

@inproceedings{icb-2018,
  author = "Nikisins, Olegs and Mohammadi, Amir and Anjos, André and
  Marcel, Sébastien",
  month = 2,
  title = "On Effectiveness of Anomaly Detection Approaches against
  Unseen Presentation Attacks in Face Anti-Spoofing",
  booktitle = "The 11th IAPR International Conference on Biometrics
  (ICB 2018)",
  year = "2018",
  url = "https://publications.idiap.ch/index.php/publications/show/3793",
  pdf = "https://www.idiap.ch/~aanjos/papers/icb-2018.pdf",
  doi= "10.1109/ICB2018.2018.00022",
  abstract = "While face recognition systems got a significant boost
  in terms of recognition performance in recent years, they are known
  to be vulnerable to presentation attacks. Up to date, most of the
  research in the field of face anti-spoofing or presentation attack
  detection was considered as a two-class classification task:
  features of bona-fide samples versus features coming from spoofing
  attempts. The main focus has been on boosting the anti-spoofing
  performance for databases with identical types of attacks across
  both training and evaluation subsets. However, in realistic
  applications the types of attacks are likely to be unknown,
  potentially occupying a broad space in the feature domain.
  Therefore, a failure to generalize on unseen types of attacks is
  one of the main potential challenges in existing anti-spoofing
  approaches. First, to demonstrate the generalization issues of
  two-class anti-spoofing systems we establish new evaluation
  protocols for existing publicly available databases. Second, to
  unite the data collection efforts of various institutions we
  introduce a challenging Aggregated database composed of 3 publicly
  available datasets: Replay-Attack, Replay-Mobile and MSU MFSD,
  reporting the performance on it. Third, considering existing
  limitations we propose a number of systems approaching a task of
  presentation attack detection as an anomaly detection, or a
  one-class classification problem, using only bona-fide features in
  the training stage. Using less training data, hence requiring less
  effort in the data collection, the introduced approach demonstrates
  a better generalization properties against previously unseen types
  of attacks on the proposed Aggregated database.",
}

%%%%%%%%%%%%
%%  2017  %%
%%%%%%%%%%%%

@misc{arxiv-2017-2,
  author = "Heusch, Guillaume and Anjos, Andr{\'{e}} and Marcel,
  S{\'{e}}bastien",
  title = "A reproducible study on remote heart rate measurement",
  journal = "arXiv",
  year = "2017",
  month = 9,
  archivePrefix = "arXiv",
  eprint = "1709.00962",
  primaryClass = "cs-se",
  addendum = {(Issued from project co-supervision)},
  url = "https://arxiv.org/abs/1709.00962",
  doi = {10.48550/arXiv.1709.00962},
  abstract = "This paper studies the problem of reproducible research
  in remote photoplethysmography (rPPG). Most of the work published
  in this domain is assessed on privately-owned databases, making it
  difficult to evaluate proposed algorithms in a standard and
  principled manner. As a consequence, we present a new, publicly
  available database containing a relatively large number of subjects
  recorded under two different lighting conditions. Also, three
  state-of-the-art rPPG algorithms from the literature were selected,
  implemented and released as open source free software. After a
  thorough, unbiased experimental evaluation in various settings, it
  is shown that none of the selected algorithms is precise enough to
  be used in a real-world scenario.",
}

@patent{beat-patent-2017,
  author = {Anjos, André AND Marcel, Sébastien},
  title = {A data-network connected server, a device, a platform and
  a method for conducting computer-executable experiments},
  year = {2017},
  month = 12,
  day = 28,
  number = {WO/2017/221049},
  type = {Patent},
  location = {CH},
  filing_num = {PCT/IB2016/053683},
  yearfiled = {2016},
  monthfiled = 6,
  dayfiled = 21,
  pat_refs = {P\&TS SA (AG, LTD.); Av. J.-J. Rousseau 4 P.O. Box 2848
  2001 Neuchâtel, CH},
  abstract = {The invention concerns a platform (1), a server (10,
    10') and a client device (20) for conducting computer-executable
    experiments. The server comprises a restricted-access memory module
    (11,11') for locally storing a data structure with numerical values
    whose access is restricted to authorized devices and/or users. The
    server is provided with an instruction receiving module (12,12')
    for receiving a list of executable instructions for conducting a
    computer-executable experiment based on numerical values with
    restricted access from the client device being not authorized to
    accessing numerical values with restricted access. The server
    comprises an execution module (13,13') for conducting the
    experiment so to produce a numerical result; and a communication
    module (12,12') for transmitting the result to the client device
  and/or to the user of the client device.},
  url = {https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2017221049}
}

@inproceedings{icml-2017-2,
  author = "Anjos, André and Günther, Manuel and de Freitas Pereira,
  Tiago and Korshunov, Pavel and Mohammadi, Amir and Marcel, Sébastien",
  month = 8,
  title = "Continuously Reproducing Toolchains in Pattern Recognition
  and Machine Learning Experiments",
  booktitle = "Thirty-fourth International Conference on Machine Learning",
  year = "2017",
  location = "Sidney, Australia",
  url = "https://publications.idiap.ch/index.php/publications/show/3666",
  pdf = "https://www.idiap.ch/~aanjos/papers/icml-2017-2.pdf",
  poster = "https://www.idiap.ch/~aanjos/posters/icml-2017-2.pdf",
  abstract = "Pattern recognition and machine learning research work
  often contains experimental results on real-world data, which
  corroborates hypotheses and provides a canvas for the development
  and comparison of new ideas. Results, in this context, are
  typically summarized as a set of tables and figures, allowing the
  comparison of various methods, highlighting the advantages of the
  proposed ideas. Unfortunately, result reproducibility is often an
  overlooked feature of original research publications, competitions,
  or benchmark evaluations. The main reason for such a gap is the
  complexity on the development of software associated with these
  reports. Software frameworks are difficult to install, maintain,
  and distribute, while scientific experiments often consist of many
  steps and parameters that are difficult to report. The increasingly
  rising complexity of research challenges make it even more
  difficult to reproduce experiments and results. In this paper, we
  emphasize that a reproducible research work should be repeatable,
  shareable, extensible, and stable, and discuss important lessons we
  learned in creating, distributing, and maintaining software and
  data for reproducible research in pattern recognition and machine
  learning. We focus on a specific use-case of face recognition and
  describe in details how we can make the recognition experiments
  reproducible in practice.",
}

@inproceedings{icml-2017-1,
  author = "Anjos, André and El Shafey, Laurent and Marcel, Sébastien",
  month = 8,
  title = "BEAT: An Open-Science Web Platform",
  booktitle = "Thirty-fourth International Conference on Machine Learning",
  year = "2017",
  location = "Sydney, Australia",
  url = "https://publications.idiap.ch/index.php/publications/show/3665",
  pdf = "https://www.idiap.ch/~aanjos/papers/icml-2017-1.pdf",
  poster = "https://www.idiap.ch/~aanjos/posters/icml-2017-1.pdf",
  abstract = "With the increased interest in computational sciences,
  machine learning (ML), pattern recognition (PR) and big data,
  governmental agencies, academia and manufacturers are overwhelmed
  by the constant influx of new algorithms and techniques promising
  improved performance, generalization and robustness. Sadly, result
  reproducibility is often an overlooked feature accompanying
  original research publications, competitions and benchmark
  evaluations. The main reasons behind such a gap arise from natural
  complications in research and development in this area: the
  distribution of data may be a sensitive issue; software frameworks
  are difficult to install and maintain; Test protocols may involve a
  potentially large set of intricate steps which are difficult to handle.

  To bridge this gap, we built an open platform for research in
  computational sciences related to pattern recognition and machine
  learning, to help on the development, reproducibility and
  certification of results obtained in the field. By making use of
  such a system, academic, governmental or industrial organizations
  enable users to easily and socially develop processing toolchains,
  re-use data, algorithms, workflows and compare results from
  distinct algorithms and/or parameterizations with minimal effort.
  This article presents such a platform and discusses some of its key
  features, uses and limitations. We overview a currently operational
  prototype and provide design insights.",
}

@inproceedings{interspeech-2017,
  author = "Cernak, Milos and Komaty, Alain and Mohammadi, Amir and
  Anjos, André and Marcel, Sébastien",
  month = 8,
  title = "Bob Speaks Kaldi",
  booktitle = "Proceedings of Interspeech",
  year = "2017",
  url = "https://publications.idiap.ch/index.php/publications/show/3623",
  pdf = "https://www.idiap.ch/~aanjos/papers/interspeech-2017.pdf",
  abstract = "This paper introduces and demonstrates Kaldi
  integration into Bob signal-processing and machine learning
  toolbox. The motivation for this integration is two-fold. Firstly,
  Bob benefits from using advanced speech processing tools developed
  in Kaldi. Secondly, Kaldi benefits from using complementary Bob
  modules, such as modulation-based VAD with an adaptive
  thresholding. In addition, Bob is designed as an open science tool,
  and this integration might offer to the Kaldi speech community a
  framework for better reproducibility of state-of-the-art research results.",
}

@misc{arxiv-2017,
  author = "André Anjos AND Laurent El-Shafey AND Sébastien Marcel",
  title = "BEAT: An Open-Source Web-Based Open-Science Platform",
  year = "2017",
  month = 4,
  archivePrefix = "arXiv",
  eprint = "1704.02319",
  primaryClass = "cs-se",
  doi = {10.48550/arXiv.1704.02319},
  url = "https://arxiv.org/abs/1704.02319",
  abstract = "With the increased interest in computational sciences,
  machine learning (ML), pattern recognition (PR) and big data,
  governmental agencies, academia and manufacturers are overwhelmed
  by the constant influx of new algorithms and techniques promising
  improved performance, generalization and robustness. Sadly, result
  reproducibility is often an overlooked feature accompanying
  original research publications, competitions and benchmark
  evaluations. The main reasons behind such a gap arise from natural
  complications in research and development in this area: the
  distribution of data may be a sensitive issue; software frameworks
  are difficult to install and maintain; Test protocols may involve a
  potentially large set of intricate steps which are difficult to
  handle. Given the raising complexity of research challenges and the
  constant increase in data volume, the conditions for achieving
  reproducible research in the domain are also increasingly difficult to meet.

  To bridge this gap, we built an open platform for research in
  computational sciences related to pattern recognition and machine
  learning, to help on the development, reproducibility and
  certification of results obtained in the field. By making use of
  such a system, academic, governmental or industrial organizations
  enable users to easily and socially develop processing toolchains,
  re-use data, algorithms, workflows and compare results from
  distinct algorithms and/or parameterizations with minimal effort.
  This article presents such a platform and discusses some of its key
  features, uses and limitations. We overview a currently operational
  prototype and provide design insights.",
}

%%%%%%%%%%%%
%%  2016  %%
%%%%%%%%%%%%

@incollection{face-spoof-2016,
  author = "Chingovska, Ivana and Erdogmus, Nesli and Anjos,
  Andr{\'{e}} and Marcel, S{\'{e}}bastien",
  month = 2,
  title = "Face Recognition Systems Under Spoofing Attacks",
  booktitle = "Face Recognition Systems Under Spoofing Attacks",
  edition = "1st edition",
  chapter = "8",
  year = "2016",
  pages = "165--194",
  publisher = "Springer International Publishing",
  doi = "10.1007/978-3-319-28501-6_8",
  addendum = {(Issued from Ph.D co-supervision)},
  abstract = "In this chapter, we give an overview of spoofing
  attacks and spoofing countermeasures for face recognition systems ,
  with a focus on visual spectrum systems (VIS) in 2D and 3D, as well
  as near-infrared (NIR) and multispectral systems . We cover the
  existing types of spoofing attacks and report on their success to
  bypass several state-of-the-art face recognition systems. The
  results on two different face spoofing databases in VIS and one
  newly developed face spoofing database in NIR show that spoofing
  attacks present a significant security risk for face recognition
  systems in any part of the spectrum. The risk is partially reduced
  when using multispectral systems. We also give a systematic
  overview of the existing anti-spoofing techniques, with an analysis
  of their advantages and limitations and prospective for future work.",
}

@article{ieee-access-2016,
  author = {Morales, Aythami AND Fierrez, Julian AND Tolosana, Ruben
    AND Ortega-Garcia, Javier AND Galbally, Javier AND Gomez-Barrero,
  Marta AND Anjos, Andr{\'{e}} AND Marcel, S{\'{e}}bastien},
  month = 11,
  title = "Keystroke Biometrics Ongoing Competition",
  journal = "IEEE Access",
  volume = "4",
  year = "2016",
  pages = "7736--7746",
  issn = "2169-3536",
  doi = "10.1109/ACCESS.2016.2626718",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-access-2016.pdf",
  abstract = "This paper presents the first Keystroke Biometrics
  Ongoing Competition (KBOC) organized to establish a reproducible
  baseline in person authentication using keystroke biometrics. The
  competition has been developed using the BEAT platform and includes
  one of the largest keystroke databases publicly available based on
  a fixed text scenario. The database includes genuine and attacker
  keystroke sequences from 300 users acquired in 4 different sessions
  distributed in a four month time span. The sequences correspond to
  the user's name and surname and therefore each user comprises an
  individual and personal sequence. As baseline for KBOC we report
  the results of 31 different algorithms evaluated according to
  performance and robustness. The systems have achieved EERs as low
  as 5.32\% and high robustness against multisession variability with
  drop of performances lower than 1\% for probes separated by months.
  The entire database is publicly available at the competition website.",
}

%%%%%%%%%%%%
%%  2015  %%
%%%%%%%%%%%%

@article{tifs-2015,
  author = "Chingovska, Ivana and Anjos, Andr{\'{e}}",
  keywords = "Biometric Verification, Counter-Measures,
  Counter-Spoofing, Liveness Detection, Replay, Spoofing Attacks",
  title = "On the use of client identity information for face anti-spoofing",
  journal = "IEEE Transactions on Information Forensics and Security,
  Special Issue on Biometric Anti-spoofing",
  addendum = {(Issued from Ph.D co-supervision)},
  volume = "10",
  number = "4",
  month = 2,
  year = "2015",
  pages = "787--796",
  doi = "10.1109/TIFS.2015.2400392",
  pdf = "https://www.idiap.ch/~aanjos/papers/tifs-2015.pdf",
  abstract = "With biometrics playing the role of a password which
  can not be replaced if stolen, the necessity of establishing
  counter-measures to biometric spoofing attacks has been recognized.
  Regardless of the biometric mode, the typical approach of
  anti-spoofing systems is to classify biometric evidence based on
  features discriminating between real accesses and spoofing attacks.
  For the first time, to the best of our knowledge, this paper
  studies the amount of client-specific information within these
  features and how it affects the performance of anti-spoofing
  systems. We make use of this information to build two
  client-specific anti-spoofing solutions, one relying on a
  generative and another one on a discriminative paradigm. The
  proposed methods, tested on a set of state-of-the-art anti-spoofing
  features for the face mode, outperform the client-independent
  approaches with up to 50\% relative improvement and exhibit better
  generalization capabilities on unseen types of spoofing attacks.",
}

%%%%%%%%%%%%
%%  2014  %%
%%%%%%%%%%%%

@incollection{eob-2014,
  author = "Chingovska, Ivana and Anjos, Andr{\'{e}} and Marcel,
  S{\'{e}}bastien",
  editor = "Z.Li, Stan and Jain, Anil",
  title = "Anti-spoofing: Evaluation Methodologies",
  booktitle = "Encyclopedia of Biometrics",
  edition = "2nd edition",
  year = "2014",
  publisher = "Springer US",
  isbn = "978-3-642-27733-7",
  doi = "10.1007/978-3-642-27733-7",
  addendum = {(Issued from Ph.D co-supervision)},
  abstract = "Following the definition of the task of the
  anti-spoofing systems to discriminate between real accesses and
  spoofing attacks, anti-spoofing can be regarded as a binary
  classification problem. The spoofing databases and the evaluation
  methodologies for anti-spoofing systems most often comply to the
  standards for binary classification problems. However, the
  anti-spoofing systems are not destined to work stand-alone, and
  their main purpose is to protect a verification system from
  spoofing attacks. In the process of combining the decision of an
  anti-spoofing and a recognition system, effects on the recognition
  performance can be expected. Therefore, it is important to analyze
  the problem of anti-spoofing under the umbrella of biometric
  recognition systems. This brings certain requirements in the
  database design, as well as adapted concepts for evaluation of
  biometric recognition systems under spoofing attacks.",
}

@incollection{eob-2014-2,
  author = "Anjos, Andr{\'{e}} AND Chingovska, Ivana AND Marcel,
  S{\'{e}}bastien",
  editor = "Z.Li, Stan AND Jain, Anil",
  title = "Anti-Spoofing: Face Databases",
  booktitle = "Encyclopedia of Biometrics",
  edition = "2nd edition",
  year = "2014",
  publisher = "Springer US",
  isbn = "978-3-642-27733-7",
  doi = "10.1007/978-3-642-27733-7_9212-2",
  addendum = {(Issued from Ph.D co-supervision)},
  abstract = "Datasets for the evaluation of face verification system
  vulnerabilities to spoofing attacks and for the evaluation of face
  spoofing countermeasures.",
}

@article{tifs-2014,
  author = "Ivana Chingovska AND André Anjos AND Sébastien Marcel",
  title = "Biometrics Evaluation Under Spoofing Attacks",
  journal = "IEEE Transactions on Information, Forensics and Security",
  year = "2014",
  month = 8,
  volume = "9",
  number = "12",
  doi = "10.1109/TIFS.2014.2349158",
  pdf = "https://www.idiap.ch/~aanjos/papers/tifs-2014.pdf",
  addendum = {(Issued from Ph.D co-supervision)},
  abstract = "While more accurate and reliable than ever, the
  trustworthiness of biometric verification systems is compromised by
  the emergence of spoofing attacks. Responding to this threat,
  numerous research publications address isolated spoofing detection,
  resulting in efficient counter-measures for many biometric modes.
  However, an important, but often overlooked issue regards their
  engagement into a verification task and how to measure their impact
  on the verification systems themselves. A novel evaluation
  framework for verification systems under spoofing attacks, called
  Expected Performance and Spoofability (EPS) framework, is the major
  contribution of this paper. Its purpose is to serve for an
  objective comparison of different verification systems with regards
  to their verification performance and vulnerability to spoofing,
  taking into account the system’s application-dependent
  susceptibility to spoofing attacks and cost of the errors. The
  convenience of the proposed open-source framework is demonstrated
  for the face mode, by comparing the security guarantee of four
  baseline face verification systems before and after they are
  secured with anti-spoofing algorithms.",
}

@incollection{hopad-2014,
  title = "Face Anti-Spoofing: Visual Approach",
  author = "André Anjos AND Jukka Komulainen AND Sébastien Marcel AND
  Abdenour Hadid and Matti Pietikainen",
  editor = "Marcel, S{\'{e}}bastien AND Nixon, Mark AND Z.Li, Stan",
  chapter = "4",
  booktitle = "Handbook of Biometric Anti-Spoofing",
  publisher = "Springer-Verlag",
  pages = "65--82",
  year = "2014",
  doi = {10.1007/978-1-4471-6524-8_4},
  abstract = "User authentication is an important step to protect
  information and in this regard face biometrics is advantageous.
  Face biometrics is natural, easy to use and less human-invasive.
  Unfortunately, recent work revealed that face biometrics is quite
  vulnerable to spoofing attacks. This chapter presents the different
  modalities of attacks to visual spectrum face recognition systems.
  We introduce public datasets for the evaluation of vulnerability of
  recognition systems and performance of counter-measures. Finally,
  we build a comprehensive view of anti-spoofing techniques for
  visual spectrum face recognition and provide an outlook of issues
  that remain unaddressed.",
}

@incollection{hopad-2014-2,
  title = "Evaluation Methodologies",
  author = "Ivana Chingovska AND André Anjos AND Sébastien Marcel",
  editor = "Marcel, S{\'{e}}bastien AND Nixon, Mark AND Z.Li, Stan",
  chapter = "10",
  pages = "185--204",
  booktitle = "Handbook of Biometric Anti-Spoofing",
  publisher = "Springer-Verlag",
  year = "2014",
  doi = "10.1007/978-1-4471-6524-8_10",
  addendum = {(Issued from Ph.D co-supervision)},
  abstract = "Following the definition of the task of the
  anti-spoofing systems to discriminate between real accesses and
  spoofing attacks, anti-spoofing can be regarded as a binary
  classification problem. The spoofing databases and the evaluation
  methodologies for anti-spoofing systems most often comply to the
  standards for binary classification problems. However the
  anti-spoofing systems are not destined to work stand-alone, and
  their main purpose is to protect a verification system from
  spoofing attacks. In the process of combining the decision of an
  anti-spoofing and a recognition system, effects on the recognition
  performance can be expected. Therefore, it is important to analyze
  the problem of anti-spoofing under the umbrella of biometric
  recognition systems. This brings certain requirements in the
  database design, as well as adapted concepts for evaluation of
  biometric recognition systems under spoofing attacks.",
}

@incollection{hopad-2014-3,
  author = "Z.Li, Stan AND Galbally, Javier AND Anjos, Andr{\'{e}}
  AND Marcel, S{\'{e}}bastien",
  editor = "Marcel, S{\'{e}}bastien AND Nixon, Mark AND Z.Li, Stan",
  title = "Evaluation Databases",
  booktitle = "Handbook of Biometric Anti-Spoofing",
  chapter = "Appendix A",
  year = "2014",
  pages = "247--278",
  publisher = "Springer-Verlag",
  isbn = "978-1-4471-6523-1",
  doi = "10.1007/978-1-4471-6524-8",
}

@article{eurasip-2014,
  author = "de Freitas Pereira, Tiago AND Komulainen, Jukka AND
  Anjos, André AND De Martino, José Mario AND Hadid, Abdenour AND
  Pietikainen, Matti and Marcel, Sébastien",
  title = "Face liveness detection using dynamic texture",
  journal = "EURASIP Journal on Image and Video Processing",
  year = "2014",
  month = 1,
  doi = "10.1186/1687-5281-2014-2",
  volume = "2014:2",
  pdf = "https://www.idiap.ch/~aanjos/papers/eurasip-2014.pdf",
  abstract = "User authentication is an important step to protect
  information, and in this context, face biometrics is potentially
  advantageous. Face biometrics is natural, intuitive, easy to use,
  and less human-invasive. Unfortunately, recent work has revealed
  that face biometrics is vulnerable to spoofing attacks using cheap
  low-tech equipment. This paper introduces a novel and appealing
  approach to detect face spoofing using the spatiotemporal (dynamic
  texture) extensions of the highly popular local binary pattern
  operator. The key idea of the approach is to learn and detect the
  structure and the dynamics of the facial micro-textures that
  characterise real faces but not fake ones. We evaluated the
  approach with two publicly available databases (Replay-Attack
  Database and CASIA Face Anti-Spoofing Database). The results show
  that our approach performs better than state-of-the-art techniques
  following the provided evaluation protocols of each database.",
}

%%%%%%%%%%%%
%%  2013  %%
%%%%%%%%%%%%

@article{iet-biometrics-2013,
  author = "André Anjos AND Murali Mohan Chakka AND Sébastien Marcel",
  title = "Motion-Based Counter-Measures to Photo Attacks in Face
  Recognition",
  journal = "IET Biometrics",
  year = "2013",
  month = 7,
  pdf = "https://www.idiap.ch/~aanjos/papers/iet-biometrics-2013.pdf",
  doi = "10.1049/iet-bmt.2012.0071",
  abstract = "Identity spoofing is a contender for high-security face
  recognition applications. With the advent of social media and
  globalized search, our face images and videos are wide-spread on
  the internet and can be potentially used to attack biometric
  systems without previous user consent. Yet, research to counter
  these threats is just on its infancy - we lack public standard
  databases, protocols to measure spoofing vulnerability and baseline
  methods to detect these attacks. The contributions of this work to
  the area are three-fold: firstly we introduce a publicly available
  PHOTO-ATTACK database with associated protocols to measure the
  effectiveness of counter-measures. Based on the data available, we
  conduct a study on current state-of-the-art spoofing detection
  algorithms based on motion analysis, showing they fail under the
  light of these new dataset. By last, we propose a new technique of
  counter-measure solely based on foreground/background motion
  correlation using Optical Flow that outperforms all other
  algorithms achieving nearly perfect scoring with an equal-error
  rate of 1.52\% on the available test data. The source code leading
  to the reported results is made available for the replicability of
  findings in this article.",
}

@inproceedings{cvpr-bw-2013,
  author = "Ivana Chingovska AND André Anjos AND Sébastien Marcel",
  title = "Anti-spoofing in action: joint operation with a
  verification system",
  booktitle = "Computer Vision and Pattern Recognition Conference -
  Biometrics Workshop",
  year = "2013",
  doi = "10.1109/CVPRW.2013.22",
  month = 6,
  pdf = "https://www.idiap.ch/~aanjos/papers/cvpr-bw-2013.pdf",
  abstract = "Besides the recognition task, today’s biometric systems
  need to cope with additional problem: spoofing attacks. Up to date,
  academic research considers spoofing as a binary classification
  problem: systems are trained to discriminate between real accesses
  and attacks. However, spoofing counter-measures are not designated
  to operate stand-alone, but as a part of a recognition system they
  will protect. In this paper, we study techniques for decisionlevel
  and score-level fusion to integrate a recognition and anti-spoofing
  systems, using an open-source framework that handles the ternary
  classification problem (clients, impostors and attacks)
  transparently. By doing so, we are able to report the impact of
  different spoofing counter-measures, fusion techniques and
  thresholding on the overall performance of the final recognition
  system. For a specific use case covering face verification,
  experiments show to what extent simple fusion improves the
  trustworthiness of the system when exposed to spoofing attacks.",
}

@inproceedings{icb-2013-1,
  author = "Tiago de Freitas Pereira AND André Anjos AND José Mario
  De Martino and Sébastien Marcel",
  title = "Can face anti-spoofing countermeasures work in a real
  world scenario?",
  booktitle = "International Conference on Biometrics 2013",
  month = 6,
  year = "2013",
  doi = "10.1109/ICB.2013.6612981",
  pdf = "https://www.idiap.ch/~aanjos/papers/icb-2013-1.pdf",
  abstract = "User authentication is an important step to protect in-
  formation and in this field face biometrics is advantageous. Face
  biometrics is natural, easy to use and less human-invasive.
  Unfortunately, recent work has revealed that face biometrics is
  vulnerable to spoofing attacks using low-tech equipments. This
  article assesses how well existing face anti-spoofing
  countermeasures can work in a more realistic condition. Experiments
  carried out with two freely available video databases (Replay
  Attack Database and CASIA Face Anti-Spoofing Database) show low
  generalization and possible database bias in the evaluated
  countermeasures. To generalize and deal with the diversity of
  attacks in a real world scenario we introduce two strategies that
  show promising results.",
}

@inproceedings{icb-2013-2,
  author = "Jukka Komulainen AND Abdenour Hadid AND Matti Pietikäinen
  AND André Anjos AND Sébastien Marcel",
  title = "Complementary Countermeasures for Detecting Scenic Face
  Spoofing Attacks",
  booktitle = "International Conference on Biometrics 2013",
  month = 6,
  year = "2013",
  pdf = "https://www.idiap.ch/~aanjos/papers/icb-2013-2.pdf",
  doi = "10.1109/ICB.2013.6612968",
  abstract = "The face recognition community has finally started
  paying more attention to the long-neglected problem of spoofing
  attacks. The number of countermeasures is gradually increasing and
  fairly good results have been reported on the publicly available
  databases. There exists no superior anti-spoofing technique due to
  the varying nature of attack scenarios and acquisition conditions.
  Therefore, it is important to find out complementary
  countermeasures and study how they should be combined in order to
  construct an easily extensible anti-spoofing framework. In this
  paper, we address this issue by studying fusion of motion and
  texture based countermeasures under several types of scenic face
  attacks. We provide an intuitive way to explore the fusion
  potential of different visual cues and show that the performance of
  the individual methods can be vastly improved by performing fusion
  at score level. The Half-Total Error Rate (HTER) of the best
  individual countermeasure was decreased from 11.2\% to 5.1\% on the
  Replay Attack Database. More importantly, we question the idea of
  using complex classification schemes in individual countermeasures,
  since nearly same fusion performance is obtained by replacing them
  with a simple linear one. In this manner, the computational
  efficiency and also probably the generalization ability of the
  resulting anti-spoofing framework are increased.",
}

@inproceedings{icb-2013-3,
  author = "I. Chingovska AND J. Yang AND Z. Lei AND D. Yi AND S. Z.
  Li AND O. Kähm AND C. Glaser AND N. Damer AND A. Kuijper AND A.
  Nouak AND J. Komulainen AND T. Pereira AND S. Gupta AND S.
  Khandelwal AND S. Bansal AND A. Rai AND T. Krishna AND D. Goyal AND
  M.-A. Waris AND H. Zhang AND I. Ahmad AND S. Kiranyaz AND M.
  Gabbouj AND R. Tronci AND M. Pili AND N. Sirena AND F. Roli AND J.
  Galbally AND J. Fierrez AND A. Pinto AND H. Pedrini AND W. S.
  Schwartz AND A. Rocha AND A. Anjos AND S. Marcel",
  title = "The 2nd Competition on Counter Measures to 2D Face
  Spoofing Attacks",
  booktitle = "International Conference on Biometrics 2013",
  month = 6,
  year = "2013",
  pdf = "https://www.idiap.ch/~aanjos/papers/icb-2013-3.pdf",
  doi = "10.1109/ICB.2013.6613026",
  abstract = "As a crucial security problem, anti-spoofing in
  biometrics, and particularly for the face modality, has achieved
  great progress in the recent years. Still, new threats arrive in
  form of better, more realistic and more sophisticated spoofing
  attacks. The objective of the 2nd Competition on Counter Measures
  to 2D Face Spoofing Attacks is to challenge researchers to create
  counter measures effectively detecting a variety of attacks. The
  submitted propositions are evaluated on the Replay-Attack database
  and the achieved results are presented in this paper.",
}

%%%%%%%%%%%%
%%  2012  %%
%%%%%%%%%%%%

@inproceedings{accv-2012,
  author = "Tiago de Freitas Pereira AND André Anjos AND José Mario
  De Martino AND Sébastien Marcel",
  title = "LBP-TOP based countermeasure against facial spoofing attacks",
  booktitle = "International Workshop on Computer Vision With Local
  Binary Pattern Variants",
  year = "2012",
  doi = "10.1007/978-3-642-37410-4_11",
  pdf = "https://www.idiap.ch/~aanjos/papers/accv-2012.pdf",
  abstract = "User authentication is an important step to protect
  informa- tion and in this field face biometrics is advantageous.
  Face biometrics is natural, easy to use and less human-invasive.
  Unfortunately, recent work has revealed that face biometrics is
  vulnerable to spoofing attacks using low-tech cheap equipments.
  This article presents a countermeasure against such attacks based
  on the LBP−TOP operator combining both space and time information
  into a single multiresolution texture descrip- tor. Experiments
  carried out with the REPLAY ATTACK database show a Half Total Error
  Rate (HTER) improvement from 15.16\% to 7.60\%.",
}

@inproceedings{acmmm-2012,
  author = "André Anjos AND Laurent El Shafey AND Roy Wallace AND
  Manuel Günther AND Chris McCool AND Sébastien Marcel",
  title = "Bob: a free signal processing and machine learning toolbox
  for researchers",
  booktitle = "ACM Multimedia 2012",
  year = "2012",
  pages = "1449--1452",
  pdf = "https://www.idiap.ch/~aanjos/papers/acmmm-2012.pdf",
  doi = "10.1145/2393347.2396517",
  abstract = "Bob is a free signal processing and machine learning
  toolbox originally developed by the Biometrics group at Idiap
  Research Institute, Switzerland. The toolbox is designed to meet
  the needs of researchers by reducing development time and
  efficiently processing data.  Firstly, Bob provides a
  researcher-friendly Python environment for rapid development.
  Secondly, efficient processing of large amounts of multimedia data
  is provided by fast C++ implementations of identified bottlenecks.
  The Python environment is integrated seamlessly with the C++
  library, which ensures the library is easy to use and extensible.
  Thirdly, Bob supports reproducible research through its integrated
  experimental protocols for several databases.  Finally, a strong
  emphasis is placed on code clarity, documentation, and thorough
  unit testing. Bob is thus an attractive resource for researchers
  due to this unique combination of ease of use, efficiency,
  extensibility and transparency.  Bob is an open-source library and
  an ongoing community effort.",
}

@inproceedings{biosig-2012,
  author = "Ivana Chingovska AND André Anjos AND Sébastien Marcel",
  title = "On the Effectiveness of Local Binary Patterns in Face
  Anti-spoofing",
  booktitle = "IEEE International Conference of the Biometrics
  Special Interest Group",
  year = "2012",
  pdf = "https://www.idiap.ch/~aanjos/papers/biosig-2012.pdf",
  isbn = "978-3-88579-290-1",
  abstract = "Spoofing attacks are one of the security traits that
  biometric recognition systems are proven to be vulnerable to. When
  spoofed, a biometric recognition system is bypassed by presenting a
  copy of the biometric evidence of a valid user. Among all biometric
  modalities, spoofing a face recognition system is particularly easy
  to perform: all that is needed is a simple photograph of the user.
  In this paper, we address the problem of detecting face spoofing
  attacks. In particular, we inspect the potential of texture
  features based on Local Binary Patterns (LBP) and their variations
  on three types of attacks: printed photographs, and photos and
  videos displayed on electronic screens of different sizes. For this
  purpose, we introduce REPLAY-ATTACK, a novel publicly available
  face spoofing database which contains all the mentioned types of
  attacks. We conclude that LBP, with ~15\% Half Total Error Rate,
  show moderate discriminability when confronted with a wide set of
  attack types.",
}

%%%%%%%%%%%%
%%  2011  %%
%%%%%%%%%%%%

@inproceedings{ijcb-2011-2,
  author = "André Anjos AND Sébastien Marcel",
  title = "Counter-Measures to Photo Attacks in Face Recognition: a
  public database and a baseline",
  booktitle = "International Joint Conference on Biometrics 2011",
  year = "2011",
  month = 10,
  pdf = "https://www.idiap.ch/~aanjos/papers/ijcb-2011-2.pdf",
  doi = "10.1109/IJCB.2011.6117503",
  abstract = "A common technique to by-pass 2-D face recognition
  systems is to use photographs of spoofed identities. Unfortunately,
  research in counter-measures to this type of attack have not
  kept-up - even if such threats have been known for nearly a decade,
  there seems to exist no consensus on best practices, techniques or
  protocols for developing and testing spoofing-detectors for face
  recognition. We attribute the reason for this delay, partly, to the
  unavailability of public databases and protocols to study solutions
  and compare results. To this purpose we introduce the publicly
  available PRINT-ATTACK database and exemplify how to use its
  companion protocol with a motion-based algorithm that detects
  correlations between the person\'s head movements and the scene
  context. The results are to be used as basis for comparison to
  other counter-measure techniques. The PRINT-ATTACK database
  contains 200 videos of real-accesses and 200 videos of spoof
  attempts using printed photographs of 50 different identities.",
}

@inproceedings{ijcb-2011,
  author = "Murali Mohan Chakka AND André Anjos AND Sébastien Marcel
  AND others",
  title = "Competition on Counter Measures to 2-D Facial Spoofing Attacks",
  booktitle = "International Joint Conference on Biometrics 2011",
  year = "2011",
  month = 10,
  doi = "10.1109/IJCB.2011.6117509",
  pdf = "https://www.idiap.ch/~aanjos/papers/ijcb-2011.pdf",
  abstract = "Spoofing identities using photographs is one of the
  most common techniques to attack 2-D face recognition systems.
  There seems to exist no comparative studies of different techniques
  using the same protocols and data. The motivation behind this
  competition is to compare the performance of different
  state-of-the-art  algorithms on the same database using a unique
  evaluation method. Six different teams from universities around the
  world have participated in the contest. Use of one or multiple
  techniques from motion, texture analysis and liveness detection
  appears to be the common trend in this competition. Most of the
  algorithms are able to clearly separate spoof attempts from real
  accesses. The results suggest the investigation of more complex attacks.",
}

%%%%%%%%%%%%
%%  2009  %%
%%%%%%%%%%%%

@article{cpc-2009,
  author = "Torres, R.C. AND Anjos, A. AND Seixas, J.M.",
  title = "Automatizing the Online Filter Test Management for a
  General-Purpose Particle Detector",
  journal = "Computer Physics Communications",
  year = "2009",
  month = 10,
  doi = "10.1016/j.cpc.2010.10.003",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/cpc-2009.pdf",
  abstract = "This paper presents a software environment to
  automatically configure and run online triggering and dataflow farms
  for the ATLAS experiment at the Large Hadron Collider (LHC). It
  provides support for a broad set of users, with distinct knowledge
  about the online triggering system, ranging from casual testers to
  final system deployers. This level of automatization improves the
  overall ATLAS TDAQ work flow for software and hardware tests and
  speeds-up system modifications and deployment.",
}

@inproceedings{nima-2010,
  author = "The ATLAS Collaboration",
  title = "ATLAS Trigger and Data Acquisition: capabilities and
  commissioning",
  year = "2010",
  volume = "617",
  number = "1",
  pages = "306--309",
  pdf = "https://www.idiap.ch/~aanjos/papers/nima-2010.pdf",
  booktitle = "11th Pisa Meeting on Advanced Detectors",
  issn = "0168-9002",
  doi = "10.1016/j.nima.2009.06.114",
  abstract = "The ATLAS trigger system is based on three levels of
  event selection that selects the physics of interest from an
  initial bunch crossing rate of 40~MHz to an output rate of
  sim200~Hz compatible with the offline computing power and storage
  capacity. During nominal LHC operations at a luminosity of
  1034~cm−2s−1, decisions must be taken every 25~ns. The LHC is
  expected to begin operations with a peak luminosity of 1031~cm−2s−1
  with far fewer number of bunches, but quickly ramp up to higher
  luminosities. Hence, the ATLAS Trigger and Data Acquisition system
  needs to adapt to the changing beam conditions preserving the
  interesting physics and detector requirements that may vary with
  these conditions.",
}

@inproceedings{chep-2009-2,
  author = "The ATLAS Collaboration",
  title = "Commissioning of the ATLAS High Level Trigger with Single
  Beam and Cosmic Rays",
  booktitle = "Computing in High Energy and Nuclear Physics, Prague,
  Czech Republic, 21 - 27 Mar 2009",
  year = "2009",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2009-2.pdf",
  abstract = "ATLAS is one of the two general-purpose detectors at
  the Large Hadron Collider (LHC). The trigger system is responsible
  for making the online selection of interesting collision events. At
  the LHC design luminosity of 10^34 cm^-2s^-1 it will need to
  achieve a rejection factor of the order of 10^-7 against random
  proton-proton interactions, while selecting with high efficiency
  events that are needed for physics analyses. After a first
  processing level using custom electronics based on FPGAs and ASICs,
  the trigger selection is made by software running on two processor
  farms, containing a total of around two thousand multi-core
  machines. This system is known as the High Level Trigger (HLT). To
  reduce the network data traffic and the processing time to
  manageable levels, the HLT uses seeded, step-wise reconstruction,
  aiming at the earliest possible rejection of background events. The
  recent LHC startup and short single-beam run provided a \'stress
  test\' of the system and some initial calibration data. Following
  this period, ATLAS continued to collect cosmic-ray events for
  detector alignment and calibration purposes. After giving an
  overview of the trigger design and its innovative features, this
  paper focuses on the experience gained from operating the ATLAS
  trigger with single LHC beams and cosmic-rays.",
}

@inproceedings{chep-2009,
  author = "The ATLAS Collaboration",
  title = "The ATLAS online High Level Trigger framework: experience
  reusing offline software components in the ATLAS trigger",
  booktitle = "Computing in High Energy and Nuclear Physics, Prague,
  Czech Republic, 21 - 27 Mar 2009",
  year = "2009",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2009.pdf",
  abstract = "Event selection in the Atlas High Level Trigger is
  accomplished to a large extent by reusing software components and
  event selection algorithms developed and tested in an offline
  environment. Many of these offline software modules are not
  specifically designed to run in a heavily multi-threaded online
  data flow environment. The Atlas High Level Trigger (HLT) framework
  based on the Gaudi and Atlas Athena frameworks, forms the interface
  layer, which allows the execution of the HLT selection and
  monitoring code within the online run control and data flow
  software. While such an approach provides a unified environment for
  trigger event selection across all of Atlas, it also poses strict
  requirements on the reused software components in terms of
  performance, memory usage and stability. Experience of running the
  HLT selection software in the different environments and especially
  on large multi-node trigger farms has been gained in several
  commissioning periods using preloaded Monte Carlo events, in data
  taking periods with cosmic events and in a short period with proton
  beams from LHC. The contribution discusses the architectural
  aspects of the HLT framework, its performance and its software
  environment within the Atlas computing, trigger and data flow
  projects. Emphasis is also put on the architectural implications
  for the software by the use of multi-core processors in the
  computing farms and the experiences gained with multi-threading and
  multi-process technologies.",
}

@inproceedings{tipp-2009,
  author = "The ATLAS Collaboration",
  title = "Configuration and Control of the ATLAS Trigger and Data
  Acquisition",
  booktitle = "The 1st international conference on Technology and
  Instrumentation in Particle Physics",
  year = "2009",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/tipp-2009.pdf",
  abstract = "ATLAS is the biggest of the experiments aimed at
  studying high-energy particle interactions at the Large Hadron
  Collider (LHC). This paper describes the evolution of the Controls
  and Configuration system of the ATLAS Trigger and Data Acquisition
  (TDAQ) from the Technical Design Report (TDR) in 2003 to the first
  events taken at CERN with circulating beams in autumn 2008. The
  present functionality and performance and the lessons learned
  during the development are outlined. At the end we will also
  highlight some of the challenges which still have to be met by
  2010, when the full scale of the trigger farm will be deployed.",
}

@inproceedings{lhc-2009,
  author = "The ATLAS Collaboration",
  title = "Atlas trigger for first physics and beyond",
  booktitle = "Physics at LHC 2008 29 September - October 4, 2008
  Split, Croatia",
  year = "2009",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/lhc-2009.pdf",
  abstract = "ATLAS is a multi-purpose spectrometer built to perform
  precision measurements of Standard Model parameters and is aiming
  at discovery of Higgs particle, Super Symmetry and possible other
  physics channels beyond Standard Model. Operating at 14 TeV center
  of mass energy ATLAS will see 40 million events per second at
  nominal luminosity with about 25 overlapping interactions. Most of
  the events are inelastic proton-proton interactions with only few
  W, Z bosons or ttbar pairs produced each second, and expectations
  for Higgs or SUSY production cross-section are much smaller than
  that. ATLAS trigger has a difficult task to select one out of 10 5
  events online and to ensure that most physics channels of interests
  are preserved for analysis. In this talk we will review the design
  of ATLAS trigger system, the trigger menu prepared for initial LHC
  run as well as for high luminosity run. The expected trigger
  performance of the base-line ATLAS physics programs will be
  reviewed and first results from the commissioning period will be
  given. The methods to measure trigger efficiencies and biases
  directly from data will be discussed.",
}

@inproceedings{acat-2009,
  author = "The ATLAS Collaboration",
  title = "ATLAS Trigger Status and Results From Commissioning Operations",
  booktitle = "Advanced Computing on High-Energy Physics 2008, Erice,
  Sicily, Italy",
  year = "2009",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/acat-2009.pdf",
  abstract = "The ATLAS trigger system is designed to select rare
  physics processes of interest from an extremely high rate of
  proton-proton collisions, reducing the LHC incoming rate of about
  107. The short LHC bunch crossing period of 25 ns and the large
  background of soft-scattering events overlapped in each bunch
  crossing pose serious challenges, both on hardware and software,
  that the ATLAS trigger must overcome in order to efficiently select
  interesting events. The ATLAS trigger consists of hardware based
  Level-1, and a two-level software based High-Level Trigger (HLT).
  Data bandwidth and processing times in the higher level triggers
  are reduced by region of interest guidance in the HLT
  reconstruction steps. High flexibility is critical in order to
  adapt to the changing luminosity, backgrounds and physics goals. It
  is achieved by the use of inclusive trigger menus and modular
  software design. Selection algorithms have been developed which
  provide the required elasticity to detect different physics
  signatures and to control the trigger rates. In this paper an
  overview of the ATLAS trigger design, status and expected
  performance, as well as the results from the on-going commissioning
  with cosmic rays and first LHC beams, is presented.",
}

%%%%%%%%%%%%
%%  2008  %%
%%%%%%%%%%%%

@inproceedings{talk-2008,
  author = "André Anjos",
  title = "Trigger Systems",
  booktitle = "Experimental High-Energy Physics and Associated
  Technologies Workshop",
  year = "2008",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/talk-2008.pptx",
  abstract = "This is an invited talk. The contents were based on the
  fundamentals of Triggering System in High-Energy Physics experiments.",
}

@inproceedings{acat-2008,
  author = "André Anjos on behalf of the ATLAS Collaboration",
  title = "The DAQ/HLT system of the ATLAS experiment",
  booktitle = "International Workshop on Advanced Computing and
  Analysis Techniques in Physics Research",
  year = "2008",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/acat-2008.pdf",
  abstract = "The DAQ/HLT system of the ATLAS experiment at CERN,
  Switzerland, is being commissioned for first collisions in 2009.
  Presently, the system is composed of an already very large farm of
  computers that accounts for about one-third of its event processing
  capacity. Event selection is conducted in two steps after the
  hardware-based Level-1 Trigger: a Level-2 Trigger processes
  detector data based on regions of interest (RoI) and an Event
  Filter operates on the full event data assembled by the Event
  Building system. The detector readout is fully commissioned and can
  be operated at its full design capacity. This places on the
  High-Level Triggers system the responsibility to maximize the
  quality of data that will finally reach the offline reconstruction
  farms. This paper brings an overview of the current ATLAS DAQ/HLT
  implementation and performance based on studies originated from its
  operation with simulated, cosmic particles and first-beam data. Its
  built-in event processing parallelism is discussed for both HLT
  levels as well as an outlook of options to improve it.",
}

@inproceedings{iprd-2008,
  author = "The ATLAS Collaboration",
  title = "Readiness of the ATLAS Trigger and Data Acquisition system
  for the first LHC beams",
  booktitle = "11th Topical Seminar On Innovative Particle And
  Radiation Detectors, Siena, Italy",
  year = "2008",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/iprd-2008.pdf",
  abstract = "The ATLAS Trigger and Data Acquisition (TDAQ) system is
  based on O(2k) processing nodes, interconnected by a multi-layer
  Gigabit network, and consists of a combination of custom
  electronics and commercial products. In its final configuration,
  O(20k) applications will provide the needed capabilities in terms
  of event selection, data flow, local storage and data monitoring.
  In preparation for the first LHC beams, many TDAQ sub-systems
  already reached the final configuration and roughly one third of
  the final processing power has been deployed. Therefore, the
  current system allows for a sensible evaluation of the performance
  and scaling properties. In this paper we introduce the ATLAS TDAQ
  system requirements and architecture and we discuss the status of
  software and hardware component. We moreover present the results of
  performance measurements validating the system design and providing
  a figure for the ATLAS data acquisition capabilities in the initial
  data taking period.",
}

@techreport{cern-2008,
  author = "The ATLAS Collaboration",
  title = "Expected Performance of the ATLAS Experiment Detector,
  Trigger, Physics",
  institution = "CERN Open Documentation",
  year = "2008",
  OPTvolume = "",
  number = "2008--020",
  pdf = "https://www.idiap.ch/~aanjos/papers/cern-2008.pdf",
  abstract = "A detailed study is presented of the expected
  performance of the ATLAS detector. The reconstruction of tracks,
  leptons, photons, missing energy and jets is investigated, together
  with the performance of b-tagging and the trigger. The physics
  potential for a variety of interesting physics processes, within
  the Standard Model and beyond, is examined. The study comprises a
  series of notes based on simulations of the detector and physics
  processes, with particular emphasis given to the data expected from
  the first years of operation of the LHC at CERN.",
}

@article{jinst-2008,
  author = "The ATLAS Collaboration",
  title = "The ATLAS Experiment at the CERN Large Hadron Collider",
  journal = "Journal of Instrumentation",
  year = "2008",
  month = 8,
  OPTvolume = "",
  number = "S08003",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/jinst-2008.pdf",
  abstract = "The ATLAS detector as installed in its experimental
  cavern at point 1 at CERN is described in this paper. A brief
  overview of the expected performance of the detector when the Large
  Hadron Collider begins operation is also presented.",
}

%%%%%%%%%%%%
%%  2007  %%
%%%%%%%%%%%%

@inproceedings{nss-2007,
  author = "The ATLAS Collaboration",
  title = "The ATLAS Event Builder",
  booktitle = "IEEE Nuclear Science Symposium and Medical Imaging Conference",
  year = "2007",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/nss-2007.pdf",
  abstract = "Event data from proton-proton collisions at the LHC
  will be selected by the ATLAS experiment in a three-level trigger
  system, which, at its first two trigger levels (LVL1+LVL2), reduces
  the initial bunch crossing rate of 40 MHz to ∼3 kHz. At this rate,
  the Event Builder collects the data from the readout system PCs
  (ROSs) and provides fully assembled events to the Event Filter
  (EF). The EF is the third trigger level and its aim is to achieve a
  further rate reduction to ∼200 Hz on the permanent storage. The
  Event Builder is based on a farm of O(100).
  ",
}

@inproceedings{eurochep-2007,
  author = "The ATLAS Collaboration",
  title = "The ATLAS trigger - high-level trigger commissioning and
  operation during early data taking",
  booktitle = "International Europhysics Conference on High Energy Physics",
  year = "2007",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/eurochep-2007.pdf",
  abstract = "The ATLAS experiment is one of the two general-purpose
  experiments due to start operation soon at the Large Hadron
  Collider (LHC). The LHC will collide protons at a centre of mass
  energy of 14~TeV, with a bunch-crossing rate of 40~MHz. The ATLAS
  three-level trigger will reduce this input rate to match the
  foreseen offline storage capability of 100-200~Hz. This paper gives
  an overview of the ATLAS High Level Trigger focusing on the system
  design and its innovative features. We then present the ATLAS
  trigger strategy for the initial phase of LHC exploitation.
  Finally, we report on the valuable experience acquired through
  in-situ commissioning of the system where simulated events were
  used to exercise the trigger chain. In particular we show critical
  quantities such as event processing times, measured in a
  large-scale HLT farm using a complex trigger menu.",
}

@inproceedings{chep-2007,
  author = "The ATLAS Collaboration",
  title = "Alignment data streams for the ATLAS Inner Detector",
  booktitle = "Computing for High-Energy Physics",
  year = "2007",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2007.pdf",
  abstract = "The ATLAS experiment uses a complex trigger strategy to
  be able to reduce the Event Filter rate output, down to a level
  that allows the storage and processing of these data. These
  concepts are described in the ATLAS Computing Model which embraces
  Grid paradigm. The output coming from the Event Filter consists of
  four main streams: physical stream, express stream, calibration
  stream, and diagnostic stream. The calibration stream will be
  transferred to the Tier-0 facilities that will provide the prompt
  reconstruction of this stream with a minimum latency of 8 hours,
  producing calibration constants of sufficient quality to allow a
  first-pass processing. The Inner Detector community is developing
  and testing an independent common calibration stream selected at
  the Event Filter after track reconstruction. It is composed of raw
  data, in byte-stream format, contained in Readout Buffers (ROBs)
  with hit information of the selected tracks, and it will be used to
  derive and update a set of calibration and alignment constants.
  This option was selected because it makes use of the Byte Stream
  Converter infrastructure and possibly gives better bandwidth usage
  and storage optimization. Processing is done using specialized
  algorithms running in the Athena framework in dedicated Tier-0
  resources, and the alignment constants will be stored and
  distributed using the COOL conditions database infrastructure. This
  work is addressing in particular the alignment requirements, the
  needs for track and hit selection, and the performance issues.",
}

@article{sbrn-2007,
  author = "Thiago Ciodaro Xavier AND André Rabello Anjos AND José
  Manoel de Seixas",
  title = "Discriminação Neural de Partículas para um Detector
  Submetido a uma Alta Taxa de Eventos",
  journal = "Learning and Nonlinear Models - Revista da Sociedade
  Brasileira de Redes Neurais (SBRN)",
  year = "2007",
  month = 10,
  volume = "4",
  number = "2",
  pages = "79--92",
  pdf = "https://www.idiap.ch/~aanjos/papers/sbrn-2007.pdf",
  abstract = "This article (written in portuguese) presents the
  results of using neural networks for the optimization of the ATLAS
  online filtering system, one of the main detectors of the particle
  collider LHC (Large Hadron Collider). The Regions of interests of
  the ATLAS energy measurer calorimeter are mapped in 100 rings of
  energy deposition, which feed a classifier neural network to
  classify them as electron or jet. For the signal pre-processing, it
  is used a relevance mapping and PCA (Principal Component Analysis)
  to compact the information, increasing the processing speed and,
  eventually, increasing the detection efficiency, with a decreasing
  of false alarm rate.",
}

@inproceedings{chep-2007-2,
  author = "The ATLAS Collaboration",
  title = "The ATLAS Trigger - Commissioning with cosmic rays",
  booktitle = "International Conference on Computing in High Energy
  and Nuclear Physics",
  year = "2007",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2007-2.pdf",
  abstract = "The ATLAS detector at CERN's LHC will be exposed to
  proton-proton collisions from beams crossing at 40 MHz. At the
  design luminosity there are roughly 23 collisions per bunch
  crossing. ATLAS has designed a three-level trigger system to select
  potentially interesting events. The first-level trigger,
  implemented in custom-built electronics, reduces the incoming rate
  to less than 100 kHz with a total latency of less than 2.5s. The
  next two trigger levels run in software on commercial PC farms.
  They reduce the output rate to 100-200 Hz. In preparation for
  collision data-taking which is scheduled to commence in May 2008,
  several cosmic-ray commissioning runs have been performed. Among
  the first sub-detectors available for commissioning runs are parts
  of the barrel muon detector including the RPC detectors that are
  used in the first-level trigger. Data have been taken with a full
  slice of the muon trigger and readout chain, from the detectors in
  one sector of the RPC system, to the second-level trigger
  algorithms and the data-acquisition system. The system is being
  prepared to include the inner-tracking detector in the readout and
  second-level trigger. We will present the status and results of
  these cosmic-ray based commissioning activities. This work will
  prove to be invaluable not only during the commissioning phase but
  also for cosmic-ray data-taking during the normal running for
  detector performance studies.",
}

@inproceedings{acat-2007,
  author = "Rodrigo Coura Torres AND José Manoel Seixas AND André
  Rabello dos Anjos AND Danilo Vannier Cunha",
  title = "Online Electron/Jet Neural High-Level Trigger over
  Indenpendent Calorimetry Information",
  booktitle = "XI International Workshop on Advanced Computing and
  Analysis Techniques in Physics Research",
  year = "2007",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/acat-2007.pdf",
  abstract = "A data volume of 60 TB/s is expected from the high LHC
  collision rate and high resolution of the ATLAS detectors. To cope
  with this bandwidth, a highly programmable, three-level online
  triggering system is under development. One of the main components
  of this system is an electron/jet discriminator that uses the
  highly segmented calorimetry information. In this work, we address
  the electron/jet discrimination at the second-level trigger by
  building a set of concentric ring sums around the energy deposition
  peak in each calorimeter segment. An Independent Component Analysis
  (ICA) on these ring sums is then performed to extract the main
  sources of the calorimeter signal. The extracted independent
  components feed the input nodes of a neural electron/jet
  discriminator. The proposed system is able to achieve higher
  detection efficiency than the current electron/jet discriminating
  system operating in ATLAS, while being fast enough to cope with the
  time restrictions of the ATLAS triggering system operation.",
}

@inproceedings{rt-2007-3,
  author = "The ATLAS Collaboration",
  title = "Integration of the Trigger and Data Acquisition systems in ATLAS",
  booktitle = "IEEE Real-time conference",
  year = "2007",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/rt-2007-3.pdf",
  abstract = "During 2006 and spring 2007, integration and
  commissioning of trigger and data acquisition (TDAQ) equipment in
  the ATLAS experimental area has progressed. Much of the work has
  focused on a final prototype setup consisting of around eighty
  computers representing a subset of the full TDAQ system. There have
  been a series of technical runs using this setup. Various tests
  have been run including ones where around 6k Level-1 pre-selected
  simulated proton-proton events have been processed in a loop mode
  through the trigger and dataflow chains. The system included the
  readout buffers containing the events, event building, second level
  and third level trigger algorithms. Quantities critical for the
  final system, such as event processing times, have been studied
  using different trigger algorithms as well as different dataflow
  components.",
}

@inproceedings{rt-2007-2,
  author = "André Anjos on behalf of the ATLAS Collaboration",
  title = "The Configuration System of the ATLAS Trigger",
  booktitle = "IEEE Real-time conference",
  year = "2007",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/rt-2007-2.pdf",
  abstract = "The ATLAS detector at CERN's LHC will be exposed to
  proton-proton collisions at a rate of 40 MHz. To reduce the data
  rate, only potentially interesting events are selected by a
  three-level trigger system. The first level is implemented in
  custom-made electronics, reducing the data output rate to less than
  100 kHz. The second and third level are software triggers with a
  final output rate of 100 to 200 Hz. A system has been designed and
  implemented that holds and records the configuration information of
  all three trigger levels at a centrally maintained location. This
  system provides consistent configuration information to the online
  trigger for the purpose of data taking as well as to the offline
  trigger simulation. The use of relational database technology
  provides a means of reliable recording of the trigger configuration
  history over the lifetime of the experiment. Tools for flexible
  browsing of trigger configurations, and for their distribution
  across the ATLAS reconstruction sites have been developed. The
  usability of this design has been demonstrated in dedicated
  configuration tests of the ATLAS level-1 Central Trigger and of a
  600-node software trigger computing farm. Further tests on a
  computing cluster which is part of the final high level trigger
  system were also successful.",
}

@inproceedings{rt-2007,
  author = "The ATLAS Collaboration",
  title = "Performance of the final Event Builder for the ATLAS Experiment",
  booktitle = "15th IEEE Real Time Conference 2007",
  year = "2007",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/rt-2007.pdf",
  abstract = "Event data from proton-proton collisions at the LHC
  will be selected by the ATLAS experiment in a three level trigger
  system, which reduces the initial bunch crossing rate of 40 MHz at
  its first two trigger levels (LVL1+LVL2) to ~3 kHz. At this rate
  the Event-Builder collects the data from all Read-Out system PCs
  (ROSs) and provides fully assembled events to the the Event-Filter
  (EF), which is the third level trigger, to achieve a further rate
  reduction to ~200 Hz for permanent storage. The Event-Builder is
  based on a farm of O(100) PCs, interconnected via Gigabit Ethernet
  to O(150) ROSs. These PCs run Linux and multi-threaded software
  applications implemented in C++. All the ROSs and one third of the
  Event-Builder PCs are already installed and commissioned. We report
  on performance tests on this initial system, which show promising
  results to reach the final data throughput required for the ATLAS
  experiment.",
}

%%%%%%%%%%%%
%%  2006  %%
%%%%%%%%%%%%

@phdthesis{phd-thesis-2006,
  author = "André Anjos",
  title = "Sistema Online de Filtragem em um Ambiente com Alta Taxa
  de Eventos",
  school = "COPPE/UFRJ",
  year = "2006",
  pdf = "https://www.idiap.ch/~aanjos/papers/phd-thesis-2006.zip",
  abstract = "The ATLAS experiment at CERN, Switzerland, will count
  on a triggering system that separates the ordinary physics from the
  one representing decays of the rare Higgs boson. The Second Level
  of such a Trigger system will be composed 1,000 computers connected
  by commodity networks, processing each event approved the First
  Level Trigger in no more than 10 milliseconds. A set of algorithms
  described via software will operate in this filtering level. Among
  them, electron detection systems play a fundamental role to the
  data acquisition since the existence of these particles can
  represent interesting physics. In this work, we present more
  efficient discrimination algorithms based on artificial neural
  networks and a compaction system which benefits from the energy
  deposit profiles of these particles in calorimeters, reaching a
  classification efficiency of 97.6\% for electrons for a false-alarm
  of only 3.2\% in jets. This detection algorithm is implemented as
  part of the experiment\'s complex software infraestructure and can
  be executed in only 125 microseconds.",
}

@article{nimb-2006,
  author = "The ATLAS Collaboration",
  title = "The ATLAS Data Acquisition and Trigger : concept, design
  and status",
  journal = "Nucl. Phys. B, Proc. Suppl.",
  year = "2006",
  month = 11,
  volume = "172",
  OPTnumber = "",
  pages = "178--182",
  pdf = "https://www.idiap.ch/~aanjos/papers/nimb-2006.pdf",
  abstract = "This article presents the base-line design and
  implementation of the ATLAS Trigger and Data Acquisition system, in
  particular the Data Flow and High Level Trigger components. The
  status of the installation and commissioning of the system is also
  presented.",
}

@article{ieee-tns-2006,
  author = "André Anjos on behalf of the ATLAS Collaboration",
  title = "Deployment of the ATLAS High-Level Trigger",
  journal = "IEEE Transactions on Nuclear Science",
  year = "2006",
  month = 8,
  volume = "53",
  OPTnumber = "",
  pages = "2144--2149",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tns-2006.pdf",
  abstract = "The ATLAS combined test beam in the second half of 2004
  saw the first deployment of the ATLAS High-Level Trigger (HLT). The
  next steps are deployment on the pre-series farms in the
  experimental area during 2005, commissioning and cosmics tests with
  the full detector in 2006 and collisions in 2007. This paper
  reviews the experience gained in the test beam, describes the
  current status and discusses the further enhancements to be made.
  We address issues related to the dataflow, integration of selection
  algorithms, testing, software distribution, installation and improvements.",
}

@article{nima-2006,
  author = "A. Anjos AND R.C. Torres AND J.M. Seixas AND B.C.
  Ferreira AND T.C. Xavier",
  title = "Neural triggering system operating on high resolution
  calorimetry information",
  journal = "Nuclear Instruments and Methods in Physics Research",
  year = "2006",
  month = 4,
  volume = "559",
  OPTnumber = "",
  pages = "134--138",
  pdf = "https://www.idiap.ch/~aanjos/papers/nima-2006.pdf",
  abstract = "This paper presents an electron/jet discriminator
  system for operating at the Second Level Trigger of ATLAS. The
  system processes calorimetry data and organizes the regions of
  interest in the calorimeter in the form of concentric ring sums of
  energy deposition, so that both signal compaction and high
  performance can be achieved. The ring information is fed into a
  feed forward neural discriminator. This implementation resulted on
  a 97\% electron detection efficiency for a false alarm of 3\%. The
  full discrimination chain could still be executed in less than 500
  microseconds.",
}

@inproceedings{chep-2006,
  author = "The ATLAS Collaboration",
  title = "Studies with the ATLAS Trigger and Data Acquisition
  Pre-Series Setup",
  booktitle = "15th International Conference on Computing In High
  Energy and Nuclear Physics",
  year = "2006",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2006.pdf",
  abstract = "The pre-series test bed is used to validate the
  technology and implementation choices by comparing the final ATLAS
  readout requirements, to the results of performance, functionality
  and stability studies. We show that all the components which are
  not running reconstruction algorithms match the final ATLAS
  requirements. For the others, we calculate the amount of time per
  event that could be allocated to run these not-yet-finalized
  algorithms. We also report on the experience gained during these
  studies while interfacing with a sub-detector for the first time at
  the experimental area.",
}

@inproceedings{chep-2006-2,
  author = "The ATLAS Collaboration",
  title = "ATLAS High Level Trigger Infrastructure, ROI Collection
  and Event Building",
  booktitle = "  15th International Conference on Computing In High
  Energy and Nuclear Physics",
  year = "2006",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2006-2.pdf",
  abstract = "We describe the base-line design and implementation of
  the Data Flow and High Level Trigger (HLT) part of the ATLAS
  Trigger and Data Acquisition (TDAQ) system. We then discuss
  improvements and generalization of the system design to allow the
  handling of events in parallel data streams and we present the
  possibility for event duplication, partial Event Building and data
  stripping. We then present tests on the deployment and integration
  of the TDAQ infrastructure and algorithms at the TDAQ
  \'pre-series\' cluster (~10\% of full ATLAS TDAQ). Finally, we
  tackle two HLT performance issues.",
}

@article{jinst-2006,
  author = "André Anjos on behalf of the ATLAS Collaboration",
  title = "A configuration system for the ATLAS trigger",
  journal = "Journal of Instrumentation, Institute of Physics
  Publishing and Sissa",
  year = "2006",
  month = 2,
  OPTvolume = "",
  number = "P05004",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/jinst-2006.pdf",
  abstract = "The ATLAS detector at CERN's Large Hadron Collider will
  be exposed to proton–proton collisions from beams crossing at 40
  MHz that have to be reduced to the few hundreds of Hz allowed by
  the storage systems. A three-level trigger system has been designed
  to achieve this goal. We describe the configuration system under
  construction for the ATLAS trigger chain. It provides the trigger
  system with all the parameters required for decision taking and to
  record its history. The same system configures the event
  reconstruction, Monte Carlo simulation and data analysis, and
  provides tools for accessing and manipulating the configuration
  data in all contexts.",
}

@inproceedings{chep-2006-3,
  author = "The ATLAS Collaboration",
  title = "Testing on a Large Scale: running the ATLAS Data
  Acquisition and High Level Trigger Software on 700 PC Nodes",
  booktitle = "Computing In High Energy and Nuclear Physics",
  year = "2006",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2006-3.doc",
  abstract = "The ATLAS Data Acquisition (DAQ) and High Level Trigger
  (HLT) software system will be comprised initially of 2000 PC nodes
  which take part in the control, event readout, second level trigger
  and event filter operations. This high number of PCs will only be
  purchased before data taking in 2007. The large CERN IT LXBATCH
  facility provided the opportunity to run in July 2005 online
  functionality tests over a period of 5 weeks on a stepwise
  increasing farm size from 100 up to 700 PC dual nodes. The
  interplay between the control and monitoring software with the
  event readout, event building and the trigger software has been
  exercised the first time as an integrated system on this large
  scale. New was also to run algorithms in the online environment for
  the trigger selection and in the event filter processing tasks on a
  larger scale. A mechanism has been developed to package the offline
  software together with the DAQ/HLT software and to distribute it
  via peer-to-peer software efficiently to this large pc cluster. The
  findings obtained during the tests lead to many immediate
  improvements in the software. Trend analysis allowed identifying
  critical areas. Running an online system on a cluster of 700 nodes
  successfully was found to be especially sensitive to the
  reliability of the farm as well as the DAQ/HLT system itself and
  the future development will concentrate on fault tolerance and stability.",
}

%%%%%%%%%%%%
%%  2005  %%
%%%%%%%%%%%%

@inproceedings{icatapp-2005-2,
  author = "The ATLAS Collaboration",
  title = "Muon Reconstruction and Identification for the Event
  Filter of the ATLAS experiment",
  booktitle = "9th ICATAPP Conference on High Energy Physics",
  year = "2005",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/icatpp-2005-2.pdf",
  abstract = "The ATLAS Trigger requires high efficiency and
  selectivity in order to keep the full physics potential of the
  experiment and to reject uninteresting processes from the 40 MHz
  event production rate of the LHC. These goals are achieved with a
  trigger composed of three sequential levels of increasing accuracy
  that have to reduce the output event rate down to ~100 Hz. This
  work focuses on muon reconstruction and identification for the
  third level (Event Filter), for which specific algorithms from the
  off-line environment have been adapted to work in the trigger
  framework. Two different strategies for accessing data (wrapped and
  seeded modes) are described and their reconstruction potential is
  then shown in terms of efficiencies, resolutions and fake muon
  rejection power.",
}

@inproceedings{icatpp-2005,
  author = "The ATLAS Collaboration",
  title = "Implementation and performance of a tau lepton selection
  within the ATLAS trigger system at the LHC",
  booktitle = "9th ICATPP Conference on Astroparticle, Particle,
  Space Physics, Detectors and Medical Physics Applications",
  year = "2005",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/icatpp-2005.pdf",
  abstract = "The ATLAS experiment at the Large Hadron Collider (LHC)
  has an interaction rate of up to 1 GHz. The trigger must
  efficiently select interesting events while rejecting the large
  amount of background. The First Level trigger will reduce this rate
  to around O(75 kHz ). Subsequently, the High Level Trigger (HLT),
  comprising the Second Level trigger and the Event Filter, will
  reduce this rate by a factor of O(1000). Triggering on taus is
  important for Higgs and SUSY searches at the LHC. In this paper tau
  trigger selections are presented based on a lepton trigger if the
  tau decays leptonically or via a dedicated tau hadron trigger if
  the tau disintegrates semileptonically. We present signal
  efficiency with the electron trigger using the data sample
  A=tau+tau=e+hadron, and rate studies obtained from the dijet sample.",
}

@inproceedings{enfpc-2005-2,
  author = "A. Anjos AND R.C. Torres AND B.C. Ferreira AND T.C.
  Xavier AND J.M Seixas AND D.O. Damazio",
  title = "Otimização do Sistema de Trigger do Segundo Nível do ATLAS
  Baseado em Calorimetria",
  booktitle = "XXVI Encontro Nacional de Física de Partículas e Campos",
  year = "2005",
  month = 10,
  pdf = "https://www.idiap.ch/~aanjos/papers/enfpc-2005-2.pdf",
  abstract = "Este trabalho apresenta um discriminador neural que
  opera sobre as quantidades calculadas pelo algoritmo T2Calo,
  responsável pela deteção elétron/jato no Segundo Nível de Filtragem
  do experimento ATLAS. Este sistema de deteção melhora a eficiência
  de deteção em quase 10 pontos percentuais, mantendo um nível de
  desempenho compatível com as restrições operacionais do sistema de
  filtragem.",
}

@inproceedings{enfpc-2005,
  author = "A. Anjos AND R.C. Torres AND B.C. Ferreira AND T.C.
  Xavier AND J.M. de Seixas",
  title = "Discriminação Neural de Elétrons no Segundo Nível de
  Trigger do ATLAS",
  booktitle = "XXVI Encontro Nacional de Física de Partículas e Campos",
  year = "2005",
  month = 10,
  pdf = "https://www.idiap.ch/~aanjos/papers/enfpc-2005.pdf",
  abstract = "Este trabalho apresenta um discriminador neural para o
  segundo nível de filtragem do ATLAS, atuando no problema de
  separação elétron/jato baseado em informações de calorimetria. Para
  reduzir a alta dimensionalidade dos dados de entrada, as regiões de
  interesse (RoI) identificadas no primeiro nível são organizadas em
  anéis concêntricos de deposição energética. Este tipo de
  pré-processamento dos dados permite eficiente compactação dos
  sinais e alcança elevada capacidade de identificar elétrons.
  Atualmente, esse sistema vem sendo portado para o ambiente de
  emulação do sistema de filtragem ATHENA, de modo a se obter uma
  avaliação realística de seu desempenho. O ambiente tem o objetivo
  de simular o comportamento do sistema de filtragem, ajudando, desta
  forma, no desenvolvimento e validação dos algoritmos. Em caráter
  comparativo, o sistema proposto foi também implementado usando a
  tecnologia DSP.",
}

@article{ieee-tns-2005-3,
  author = "The ATLAS Collaboration",
  title = "Overview of the High-Level Trigger Electron and Photon
  Selection for the ATLAS Experiment at the LHC",
  journal = "IEEE Transactions Nuclear Sciences (2005)",
  year = "2005",
  month = 6,
  volume = "53",
  OPTnumber = "",
  pages = "2839--2843",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tns-2005-3.pdf",
  abstract = "The ATLAS experiment at the Large Hadron Collider (LHC)
  will face the challenge of efficiently selecting interesting
  candidate events in pp collisions at 14 TeV center-of-mass energy,
  whilst rejecting the enormous number of background events. The
  High-Level Trigger (HLT = second level trigger and Event Filter),
  which is a software based trigger will need to reduce the level-1
  output rate of ~75 kHz to ~200 Hz written out to mass storage. In
  this talk an overview of the current physics and system performance
  of the HLT selection for electrons and photons is given. The
  performance has been evaluated using Monte Carlo simulations and
  has been partly demonstrated in the ATLAS testbeam in 2004. The
  efficiency for the signal channels, the rate expected for the
  selection, the global data preparation and execution times will be
  highlighted. Furthermore, some physics examples will be discussed
  to demonstrate that the triggers are well adapted for the physics
  programme envisaged at the LHC.",
}

@article{ieee-tns-2005-2,
  author = "The ATLAS Collaboration",
  title = "Implementation and Performance of the Seeded
  Reconstruction for the ATLAS Event Filter Selection Software",
  journal = "IEEE Trans. Nucl. Sciences",
  year = "2005",
  month = 6,
  volume = "53 (2007)",
  pages = "864--869",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-2005-2.pdf",
  abstract = "ATLAS is one of the four LHC experiments that will
  start data taking in 2007, designed to cover a wide range of
  physics topics. The ATLAS trigger system has to cope with a rate of
  40 MHz and 23 interactions per bunch crossing. It is divided in
  three different levels. The first one (hardware based) provides a
  signature that is confirmed by the the following trigger levels
  (software based) by running a sequence of algorithms and validating
  the signal step by step, looking only to the region of the space
  indicated by the first trigger level (seeding). In this paper, the
  performance of one of these sequences that run at the Event Filter
  level (third level) and is composed of clustering at the
  calorimeter, track reconstruction and matching.",
}

@article{ieee-tns-2005,
  author = "The ATLAS Collaboration",
  title = "ATLAS DataFlow: the Read-Out Subsystem, Results from
  Trigger and Data-Acquisition System Testbed Studies and from Modeling",
  journal = "IEEE Trans. Nucl. Sciences",
  year = "2005",
  month = 6,
  volume = "53 (2006)",
  pages = "912--917",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tns-2005.pdf",
  abstract = "In the ATLAS experiment at the LHC, the output of
  readout hardware specific to each subdetector will be transmitted
  to buffers, located on custom made PCI cards (ROBINs). The data
  consist of fragments of events accepted by the first-level trigger
  at a maximum rate of 100 kHz. Groups of four ROBINs will be hosted
  in about 150 Read-Out Subsystem (ROS) PCs. Event data are forwarded
  on request via Gigabit Ethernet links and switches to the
  second-level trigger or to the Event builder. In this paper a
  discussion of the functionality and real-time properties of the ROS
  is combined with a presentation of measurement and modelling
  results for a testbed with a size of about 20\% of the final DAQ
  system. Experimental results on strategies for optimizing the
  system performance, such as utilization of different network
  architectures and network transfer protocols, are presented for the
  testbed, together with extrapolations to the full system.",
}

@inproceedings{rt-2005,
  author = "André Anjos on behalf of the ATLAS Collaboration",
  title = "Configuration of the ATLAS trigger",
  booktitle = "14th IEEE NPSS Real Time Conference",
  year = "2005",
  month = 6,
  pages = "990--994",
  pdf = "https://www.idiap.ch/~aanjos/papers/rt-2005.pdf",
  abstract = "The ATLAS detector at CERN's LHC will be exposed to
  proton-proton collisions at a rate of 40 MHz. In order to reduce
  the data rate to about 200 Hz, only potentially interesting events
  are selected by a three-level trigger system. Its first level is
  implemented in electronics and firmware whereas the higher trigger
  levels are based on software. To prepare the full trigger chain for
  the online event selection according to a certain strategy, a
  system is being set up that provides the relevant configuration
  information - e.g. values for hardware registers in level-1 or
  parameters of high-level trigger algorithms - and stores the
  corresponding history. The same information is used to configure
  the offline trigger simulation. In this presentation an overview of
  the ATLAS trigger system is given concentrating on the event
  selection strategy and its description. The technical
  implementation of the configuration system is summarized.",
}

%%%%%%%%%%%%
%%  2004  %%
%%%%%%%%%%%%

@inproceedings{nss-2004-3,
  author = "The ATLAS Collaboration",
  title = "Implementation and Performance of the High Level Trigger
  Electron and Photon Selection for the ATLAS Experiment at the LHC",
  booktitle = "IEEE Nuclear Science Symposium and Medical Imaging Conference",
  year = "2004",
  month = 10,
  pdf = "https://www.idiap.ch/~aanjos/papers/nss-2004-3.pdf",
  abstract = "The ATLAS experiment at the Large Hadron Collider (LHC)
  will face the challenge of efficiently selecting interesting
  candidate events in pp collisions at 14 TeV center of mass energy,
  while rejecting the enormous number of background events, stemming
  from an interaction rate of up to 10^9 Hz. The First Level trigger
  will reduce this rate to around O(100 kHz). Subsequently, the High
  Level Trigger (HLT), which is comprised of the Second Level trigger
  and the Event Filter, will need to further reduce this rate by a
  factor of O(10^3). The HLT selection is software based and will be
  implemented on commercial CPUs, using a common framework built on
  the standard ATLAS object oriented software architecture. In this
  paper an overview of the current implementation of the selection
  for electrons and photons in the HLT is given. The performance of
  this implementation has been evaluated using Monte Carlo
  simulations in terms of the efficiency for the signal channels,
  rate expected for the selection, data preparation times, and
  algorithm execution times. Besides the efficiency and rate
  estimates, some physics examples will be discussed, showing that
  the triggers are well adapted for the physics programme envisaged
  at LHC. The electron and photon trigger software is also being
  exercised at the ATLAS 2004 Combined Test Beam, where components
  from all ATLAS subdetectors are taking data together along the H8
  SPS extraction line; from these tests a validation of the selection
  architecture chosen in a real on-line environment is expected.",
}

@inproceedings{nss-2004-2,
  author = "The ATLAS Collaboration",
  title = "Design, deployment and functional tests of the on-line
  Event Filter for the ATLAS experiment at LHC",
  booktitle = "Nuclear Science Symposium and Medical Imaging Conference",
  year = "2004",
  month = 10,
  pdf = "https://www.idiap.ch/~aanjos/papers/nss-2004-2.pdf",
  abstract = "The Event Filter selection stage is a fundamental
  component of the ATLAS Trigger and Data Acquisition architecture.
  Its primary function is the reduction of data flow and rate to
  values acceptable by the mass storage operations and by the
  subsequent off-line data reconstruction and analysis steps. The
  computing instrument of the EF is generally organized as a set of
  independent sub-farms, each connected to one output of the Event
  Builder switch fabric. Each sub-farm comprises a number of
  processors analyzing several complete events in parallel. This
  paper describes the design of the ATLAS EF system, its deployment
  in the 2004 ATLAS combined test beam together with some examples of
  integrating selection and monitoring algorithms. Since the
  processing algorithms are not specially designed for EF but are
  inherited as much as possible from the off-line ones, special
  emphasis is reserved to system reliability and data security, in
  particular for the case of failures in the processing algorithms.
  Another key design element has been system modularity and
  scalability. The EF shall be able to follow technology evolution
  and should allow for using additional processing resources possibly
  remotely located.",
}

@inproceedings{nss-2004,
  author = "The ATLAS Collaboration",
  title = "Online Muon Reconstruction in the ATLAS Level-2 trigger system",
  booktitle = "Nuclear Science Symposium and Medical Imaging Conference",
  year = "2004",
  OPTvolume = "",
  OPTnumber = "",
  OPTpages = "",
  pdf = "https://www.idiap.ch/~aanjos/papers/nss-2004.pdf",
  abstract = "To cope with the 40 MHz event production rate of LHC,
  the trigger of the ATLAS experiment selects the events in three
  sequential steps of increasing complexity and accuracy whose final
  results are close to the offline reconstruction. The Level-1,
  implemented with custom hardware, identifies physics objects within
  Regions of Interests and operates a first reduction of the event
  rate to 75 KHz. The higher trigger levels provide a software based
  event selection which further reduces the event rate to about 100
  Hz. This paper presents the algorithm (muFast) employed at Level-2
  to confirm the muon candidates flagged by the Level-1. muFast
  identifies hits of muon tracks inside the Muon Spectrometer and
  provides a precise measurement of the muon momentum at the
  production vertex. The algorithm must process the Level-1 muon
  output rate (~20 KHz), thus a particular care has been used for its
  optimization. The result is a very fast track reconstruction
  algorithm with good physics performances which, in some cases,
  approach those of the offline reconstruction: it computes the pT of
  prompt muons with a resolution of 5.5\% at 6 GeV and 4.0\% at 20
  GeV and with an efficiency of about 95\%. The algorithm requires an
  overall execution time of ~1 ms on a 100 SpecInts95 machine.",
}

@inproceedings{chep-2004-2,
  author = "The ATLAS Collaboration",
  title = "Performance of the ATLAS DAQ DataFlow system",
  booktitle = "Computing in High Energy Physics and Nuclear Physics",
  year = "2004",
  month = 10,
  doi = "10.5170/CERN-2005-002.91",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2004-2.pdf",
  abstract = "The baseline DAQ architecture of the ATLAS Experiment
  at LHC is introduced and its present implementation and the
  performance of the DAQ components as measured in a laboratory
  environment are summarized. It will be shown that the discrete
  event simulation model of the DAQ system, tuned using these
  measurements, does predict the behaviour of the prototype
  configurations well, after which, predictions for the final ATLAS
  system are presented. With the currently available hardware and
  software, a system using ~140 ROSs with 3GHz single cpu, ~100 SFIs
  with dual 2.4 GHz cpu and ~500 L2PUs with dual 3.06 GHz cpu.",
}

@inproceedings{chep-2004,
  author = "The ATLAS Collaboration",
  title = "Portable Gathering System for Monitoring and Online
  Calibration at ATLAS",
  booktitle = "Computing in High Energy Physics and Nuclear Physics 2004",
  year = "2004",
  month = 10,
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2004.pdf",
  abstract = "During the runtime of any experiment, a central
  monitoring system that detects problems as soon as they appear has
  an essential role. In a large experiment, like ATLAS, the online
  data acquisition system is distributed across the nodes of large
  farms, each of them running several processes that analyse a
  fraction of the events. In this architecture, it is necessary to
  have a central process that collects all the monitoring data from
  the different nodes, produces full statistics histograms and
  analyses them. In this paper we present the design of such a
  system, called the gatherer. It allows to collect any monitoring
  object, such as histograms, from the farm nodes, from any process
  in the DAQ, trigger and reconstruction chain. It also adds up the
  statistics, if required, and processes user defined algorithms in
  order to analyse the monitoring data. The results are sent to a
  centralized display, that shows the information online, and to the
  archiving system, triggering alarms in case of problems. The
  innovation of this system is that conceptually it abstracts several
  underlying communication protocols, being able to talk with
  different processes using different protocols at the same time and,
  therefore, providing maximum flexibility. The software is easily
  adaptable to any trigger-DAQ system. The first prototype of the
  gathering system has been implemented for ATLAS and has been
  running during this year\'s combined test beam. An evaluation of
  this first prototype will also be presented.",
}

@inproceedings{enfpc-2004,
  author = "A. Anjos AND J.M. Seixas",
  title = "Os Filtros de Alto Nível do Experimento ATLAS",
  booktitle = "XXVI Encontro Nacional de Física de Partículas e Campos",
  year = "2004",
  month = 8,
  pdf = "https://www.idiap.ch/~aanjos/papers/enfpc-2004.pdf",
  abstract = "O Experimento ATLAS conta com um sistema de Filtragem
  bastante complexo e dividido em 4 grandes sub-sistemas: (i) O
  Primeiro Nível de Filtragem que realiza os primeiros passos da
  seleção de eventos na cadeia de filtragem; (ii) O Software Online,
  responsável pelas áreas de controle e operação do sistema;(iii) O
  Sistema de Fluxo de Dados (Dataflow) que coordena a transmissão e
  armazenamento dos dados do detetor do experimento; (iv) Os Filtros
  de Alto Nível, que implementam os algoritmos de discriminação,
  representando o topo da cadeia de seleção de eventos no ATLAS.

  Para aumentar a portabilidade entre os algoritmos de filtragem
  desenvolvidos por toda a comunidade do experimento, os
  desenvolvedores dos Filtros de Alto Nível (ou simplesmente HLT;
  High-Level Triggers)  propuseram a reutilização do ambiente de
  programação online Athena dentro do sistema que operará em tempo
  real. Para tal, o HLT utiliza as ferramentas propostas pelo
  sub-sistema de Fluxo de Dados para  coordenar as operações da
  transferência de informação para dentro e para fora dos nós de
  processamento sistema. Dentre outras restrições, o produto final
  deverá ser suficientemente rápido e operável em tarefas
  concorrentes em máquinas (SMP) com vários processadores rodando
  Linux.  Neste trabalho apresentamos alguns dos problemas e soluções
  encontrados pelo grupo no desenvolvimento e teste do conjunto de
  bibliotecas que compõe o HLT.",
}

@article{ieee-tns-2004-7,
  author = "J.T. Baines AND C.P. Bee AND A. Bogaerts AND M. Bosman
  AND D. Botterill AND B. Caron AND A. Anjos AND F. Etienne AND S.
  González AND K. Karr AND W. Li AND C. Meessen AND G. Merino AND A.
  Negri AND J. L. Pinfold AND P. Pinto AND Z. Qian AND F. Touchard
  AND P. Werner AND S. Wheeler AND F.J. Wickens AND W. Wiedenmann AND
  G. Zobernig",
  title = "An Overview of the ATLAS High-Level Trigger Dataflow and
  Supervision",
  journal = "IEEE Transaction on Nuclear Science",
  year = "2004",
  month = 6,
  volume = "51",
  number = "3",
  pages = "361--366",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tns-2004-7.pdf",
  abstract = "",
}

@article{ieee-tns-2004-6,
  author = "André Anjos on behalf of the ATLAS Collaboration",
  title = "The Second Level Trigger of the ATLAS Experiment at CERN's LHC",
  journal = "IEEE Transaction on Nuclear Science",
  year = "2004",
  month = 7,
  volume = "51",
  number = "3",
  pages = "909--914",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tns-2004-6.pdf",
  abstract = "The Trigger System of the ATLAS experiment reduces the
  rate of events produced by proton-proton collisions at CERN's Large
  Hadron Collider (LHC) in three successive steps from 40 MHz to ~
  100, 1 and 0.2 kHz respectively. The ATLAS Second Level Trigger is
  original in several ways. It makes use of information provided by
  the First Level Trigger which identifies Regions of Interest (RoI)
  indicating where the most significant activity has occurred within
  the detector. Accessing detector data in RoIs only reduces the
  estimated 100 Gbytes/s data rate by a factor 100. Appart from a
  custom interface to acquire the RoI information, the Second Level
  Trigger is implemented in software. Another cost saving approach is
  the development of Trigger Selection software in an offline
  environment using a common framework for the High Level Trigger and
  Reconstruction Software. Consequently, the Second Level Trigger
  draws on software developed in two largely independant domains:
  real time oriented dataflow software combined with offline
  selection software. In this paper we report on experience gained
  and results obtained with second generation prototype software of
  both domains. Test of the performance of the data collection have
  been carried out on testbeds consisting of PCs running Linux and
  interconnected by Gbit Ethernet switches. The selection software
  has been tested using simulated detector data preloaded in detector
  readout buffers.",
}

@article{ieee-tns-2004-5,
  author = "The ATLAS Collaboration",
  title = "Algorithms for the ATLAS high-level trigger",
  journal = "IEEE Transactions on Nuclear Science",
  year = "2004",
  month = 6,
  volume = "51",
  number = "3",
  pages = "367--374",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tns-2004-5.pdf",
  abstract = "Following rigorous software design and analysis
  methods, an object-based architecture has been developed to derive
  the second- and third-level trigger decisions for the future ATLAS
  detector at the LHC. The functional components within this system
  responsible for generating elements of the trigger decisions are
  algorithms running within the software architecture. Relevant
  aspects of the architecture are reviewed along with concrete
  examples of specific algorithms and their performance in
  \'vertical\' slices of various physics selection strategies."
}

@article{ieee-tns-2004-4,
  author = "The ATLAS Collaboration",
  title = "The base-line DataFlow system of the ATLAS Trigger and DAQ",
  journal = "IEEE Transactions on Nuclear Science",
  year = "2004",
  month = 6,
  volume = "51",
  number = "3",
  pages = "470--475",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tns-2004-4.pdf",
  abstract = "The base-line design and implementation of the ATLAS
  DAQ DataFlow system is described. The main components realizing the
  DataFlow system, their interactions, bandwidths and rates are being
  discussed and performance measurements on a 10\% scale prototype
  for the final Atlas TDAQ DataFlow system are presented. This
  prototype is a combination of custom design components and of
  multi-threaded software applications implemented in C++ and running
  in a Linux environment on commercially available PCs interconnected
  by a fully switched gigabit Ethernet network.",
}

@article{ieee-tns-2004-3,
  author = "The ATLAS Collaboration",
  title = "ATLAS TDAQ data collection software",
  journal = "IEEE Transactions on Nuclear Science",
  year = "2004",
  month = 6,
  volume = "51",
  OPTnumber = "",
  pages = "585--590",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tns-2004-3.pdf",
  abstract = "The DataCollection (DC) is a subsystem of the ATLAS
  Trigger and DAQ system. It is responsible for the movement of event
  data from the ReadOut subsystem to the Second Level Trigger and to
  the Event Filter. This functionality is distributed on several
  software applications running on Linux PCs interconnected with
  Gigabit Ethernet. For the design and implementation of these
  applications a common approach has been adopted. This approach
  leads to the design and implementation of a common DC software
  framework providing a suite of common services.",
}

@article{ieee-tns-2004-2,
  author = "The ATLAS Collaboration",
  title = "Studies for a common selection software environment in
  ATLAS : from the Level-2 Trigger to the offline reconstruction",
  journal = "IEEE Transactions on Nuclear Science",
  year = "2004",
  month = 6,
  volume = "51",
  number = "3",
  pages = "915--920",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tns-2004-2.pdf",
  abstract = "The ATLAS High Level Trigger\'s primary function of
  event selection will be accomplished with a Level-2 trigger farm
  and an Event Filter farm, both running software components
  developed in the Atlas offline reconstruction framework. While this
  approach provides a unified software framework for event selection,
  it poses strict requirements on offline components critical for the
  Level-2 trigger. A Level-2 decision in Atlas must typically be
  accomplished within 10 ms and with multiple event processing in
  concurrent threads. In order to address these constraints,
  prototypes have been developed that incorporate elements of the
  Atlas Data Flow -, High Level Trigger -, and offline framework
  software. To realize a homogeneous software environment for offline
  components in the High Level Trigger, the Level-2 Steering
  Controller was developed. With electron/gamma- and muon-selection
  slices it has been shown that the required performance can be
  reached, if the offline components used are carefully designed and
  optimized for the application in the High Level Trigger."
}

@article{nima-2004,
  author = "The ATLAS Collaboration",
  title = "Architecture of the ATLAS high level trigger event
  selection software",
  journal = "Nucl. Instrum. Methods Phys. Res.",
  year = "2004",
  month = 2,
  volume = "518",
  number = "1--2",
  pages = "537--541",
  pdf = "https://www.idiap.ch/~aanjos/papers/nima-2004.pdf",
  abstract = "The ATLAS High Level Trigger (HLT) consists of two
  selection steps: the second level trigger and the event filter.
  Both will be implemented in software, running on mostly commodity
  hardware. Both levels have a coherent approach to event selection,
  so a common core software framework has been designed to maximize
  this coherency, while allowing sufficient flexibility to meet the
  different interfaces and requirements of the two different levels.
  The approach is extended further to allow the software to run in an
  off-line simulation and reconstruction environment for the purposes
  of development. This paper describes the architecture and high
  level design of the software.",
}

@article{ieee-tns-2004,
  author = "The ATLAS Collaboration",
  title = "An Overview of Algorithms for the ATLAS High Level Trigger",
  journal = "IEEE Transactions on Nuclear Science",
  year = "2003",
  month = 6,
  volume = "51",
  number = "3 (2004)",
  pages = "367--374",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tns-2004.pdf",
  abstract = "Following rigorous software design and analysis
  methods, an object-based architecture has been developed to derive
  the second- and third-level trigger decisions for the future ATLAS
  detector at the LHC. The functional components within this system
  responsible for generating elements of the trigger decisions are
  algorithms running within the software architecture. Relevant
  aspects of the architecture are reviewed along with concrete
  examples of specific algorithms.",
}

%%%%%%%%%%%%
%%  2003  %%
%%%%%%%%%%%%

@inproceedings{astro-2003,
  author = "The ATLAS Collaboration",
  title = "Architecture of the ATLAS online physics-selection
  software at LHC",
  booktitle = "Conference on Astroparticle, Particle, Space Physics,
  Detectors and Medical Physics Applications",
  year = "2003",
  pdf = "https://www.idiap.ch/~aanjos/papers/astro-2003.pdf",
  abstract = "A filtragem de eventos no experimento ATLAS é
  organizada em dois níveis distintos: o Segundo Nível de Filtragem e
  e Filtro de Eventos. Um enfoque unificado para selecionar eventos
  em ambos os níveis foi escolhido. Desta forma, um conjunto de
  rotinas de base foi projetada para maximizar o compartilhamento das
  interfaces e componentes offline, ainda que mantendo uma
  flexibilidade suficientemente grande para atender  aos requisitos
  operacionais do Sistema de Filtragem, notavelmente aqueles
  relacionados ao desempenho e robustez. Este artigo descreve a
  arquitetura e o projeto do sistema de seleção de eventos e mostra
  como esta implementação é compatível com os desafios do experimento.",
}

@inproceedings{elhc-2003,
  author = "The ATLAS Collaboration",
  title = "The baseline dataflow system of the ATLAS trigger and DAQ",
  booktitle = "  9th Workshop on Electronics for LHC Experiments",
  year = "2003",
  pdf = "https://www.idiap.ch/~aanjos/papers/elhc-2003.pdf",
  abstract = "In this paper the baseline design of the ATLAS High
  Level Trigger and Data Acquisition system with respect to the
  DataFlow aspects, as presented in the recently submitted ATLAS
  Trigger/DAQ/Controls Technical Design Report [1], is reviewed and
  recent results of testbed measurements and from modelling are discussed.",
}

@techreport{cern-tdaq-tdr-2003,
  author = "The ATLAS Collaboration",
  title = "The ATLAS HLT, DAQ and DCS Technical Design Report",
  institution = "CERN Publication",
  year = "2003",
  pdf = "https://www.idiap.ch/~aanjos/papers/cern-tdaq-tdr-2003.pdf",
  abstract = "This document contains the \'blue-print\'
  specifications of the Trigger/DAQ systems of ATLAS.",
}

@article{nima-2003,
  author = "Anjos, A. AND Seixas, J.M.",
  title = "Neural particle discrimination for triggering interesting
  physics channels with calorimetry data",
  journal = "Nuclear Instruments And Methods In Physics Research A -
  Accelerators, Spectrometers, Detectors And Associated Equipament",
  year = "2003",
  month = 8,
  volume = "502",
  pages = "713--715",
  doi = "10.1016/S0168-9002(03)00553-9",
  pdf = "https://www.idiap.ch/~aanjos/papers/nima-2003.pdf",
  abstract = "This article introduces a triggering scheme for high
  input rate processors, based on neural networks. The technique is
  applied to the Electron/Jet discrimination problem, present at the
  second level trigger of the ATLAS experiment, being constructed at
  CERN. The proposed solution outperforms the scheme adopted nowadays
  at CERN, both in discrimination efficiency and performance,
  becoming a candidate algorithm for implementation at the experiment.",
}

@inproceedings{chep-2003-4,
  author = "The ATLAS Collaboration",
  title = "The DataFlow System of the ATLAS Trigger and DAQ",
  booktitle = "Conference for Computing in High-Energy and Nuclear Physics",
  year = "2003",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2003-4.pdf",
  abstract = "The baseline design and implementation of the DataFlow
  system, to be documented in the ATLAS DAQ/HLT Technical Design
  Report in summer 2003, will be presented. Empahsis will be placed
  on the system performance and scalability based on the results from
  prototyping studies which have maximised the use of commercially
  available hardware.",
}

@inproceedings{chep-2003-3,
  author = "The ATLAS Collaboration",
  title = "A New Implementation of the Region-of-Interest Strategy
  for the ATLAS Second Level Trigger",
  booktitle = "Conference for Computing in High-Energy and Nuclear Physics",
  year = "2003",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2003-3.pdf",
  abstract = "Among the many challenges presented by the future ATLAS
  detector at the LHC are the high data taking rate and volume and
  the derivation of a rapid trigger decision with limited resources.
  To address this challenge within the ATLAS second level trigger
  system, a Region-of-Interest mechanism has been adopted which
  dramatically reduces the relevant fiducial volume necessary to be
  readout and processed to small regions guided by the hardware-based
  first level trigger. Software ha s been developed to allow fast
  translation between arbitrary geometric regions and identifiers of
  small collections of the event data. This facilitates on-demand
  data retrieval and collection building. The system is optimized to
  minimize the amount of data transferred and unnecessary building of
  complex objects. Detail s of the design and implementation are
  presented along with preliminary performance results.",
}

@inproceedings{chep-2003-2,
  author = "The ATLAS Collaboration",
  title = "The Algorithm Steering and Trigger Decision mechanism of
  the ATLAS High Level Trigger",
  booktitle = "Conference for Computing in High-Energy and Nuclear Physics",
  year = "2003",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2003-2.pdf",
  abstract = "Given the extremely high output rate foreseen at LHC
  and the general-purpose nature of ATLAS experiment, an efficient
  and flexible way to select events in the High Level Trigger is
  needed. An extremely flexible solution is proposed that allows for
  early rejection of unwanted events and an easily configurable way
  to choose algorithms and to specify the criteria for trigger
  decisions. It is implemented in the standard ATLAS object-oriented
  software framework, Athena. The early rejection is achieved by
  breaking the decision process down into sequential steps. The
  configuration of each step defines sequences of algorithms which
  should be used to process the data, and \'trigger menus\' that
  define which physics signatures must be satisfied to continue on to
  the next step, and ultimately to accept the event. A navigation
  system has been built on top of the standard Athena transient store
  (StoreGate) to link the event data together in a tree-like
  structure. This is fundamental to the seeding mechanism, by which
  data from one step is presented to the next. The design makes it
  straightforward to utilize existing off-line reconstruction data
  classes and algorithms when they are suitable",
}

@inproceedings{chep-2003-1,
  author = "The ATLAS Collaboration",
  title = "Experience with multi-threaded C++ applications in the
  ATLAS dataflow software",
  booktitle = "Conference for Computing in High-Energy and Nuclear Physics",
  year = "2003",
  pdf = "https://www.idiap.ch/~aanjos/papers/chep-2003-1.pdf",
  abstract = "The DataFlow is sub-system of the ATLAS data
  acquisition responsible for the reception, buffering and subsequent
  movement of partial and full event data to the higher level
  triggers: Level 2 and Event Filter. The design of the software is
  based on OO methodology and its implementation relies heavily on
  the use of posix threads and the Standard Template Library. This
  article presents our experience with Linux, posix threads and the
  Standard Template Library in the real time environment of the ATLAS
  data flow.",
}

%%%%%%%%%%%%
%%  2001  %%
%%%%%%%%%%%%

@inproceedings{enfpc-2001,
  author = "Anjos, A. AND Seixas, J.M.",
  title = "Redes Neurais especialistas para a separação Elétron-Jato
  usando Calorímetros multi-camadas e multi-segmentados",
  booktitle = "XXII Encontro Nacional de Física de Partículas e Campos",
  year = "2001",
  pdf = "https://www.idiap.ch/~aanjos/papers/enfpc-2001.pdf",
  abstract = "O experimento ATLAS estará operacional no ano de 2006.
  O objetivo principal deste experimento é a deteção do bóson de
  Higgs, usando entre outros tipos de detetores, calorímetros. Um dos
  canais de deteção mais importantes no experimento é o de elétrons
  com alta energia transversa, representando de 30 a 40\% do total
  das assinaturas a serem analisadas pelo Sistema de Filtragem. Jatos
  (de partículas) confundem-se comumente com elétrons pela forma que
  interagem com os calorímetros. Neste trabalho, apresentamos um
  sistema de discriminação elétron-jato baseado em redes neurais
  especialistas, utilizando os dados dos calorímetros do ATLAS. Este
  sistema, depois de treinado, compacta o espaço de variáveis de
  entrada (células dos calorímetros) em um subespaço que mantém os
  aspectos necessários para uma deteção eficiente de elétrons. Os
  resultados apresentados se mostram melhores que os resultados
  obtidos usando-se técnicas desenvolvidas no CERN, com o mesmo objetivo.",
}

@phdthesis{msc-thesis-2001,
  author = "André Anjos",
  title = "Sistema neuronal rápido de decisão baseado em calorimetria
  de altas energias",
  school = "COPPE/UFRJ",
  year = "2001",
  pdf = "https://www.idiap.ch/~aanjos/papers/msc-thesis-2001.pdf",
  abstract = "This work (written in portuguese) develops a fast
  neural classifier for high energy particle discrimination
  (electron/jet) at the second level trigger of ATLAS, at CERN,
  Switzerland. The classifier is fed by the information from one of
  the ATLAS detectors, the calorimeter, a highly segmented detector
  which measures the energy of particles with high resolution. The
  information is preprocessed in a clever way, by building concentric
  energy ring sums, which reduces significantly the input
  dimensionality. Despite the high information compactation rate, the
  designed system achieves a very high discrimination efficiency
  (97\% for electrons and 95,1\% for jets), outperforming the
  classical solution implemented nowadays at the second level
  trigger. A system implementation on a fast digital signal processor
  (DSP) is presented, and its performance is evaluated in both speed
  and accuracy.",
}

%%%%%%%%%%%%
%%  2000  %%
%%%%%%%%%%%%

@inproceedings{enfpc-2000,
  author = "André Rabello dos Anjos AND José Manoel de Seixas",
  title = "Mapeamento em anéis para uma separação neuronal
  elétron-jato usando calorímetros multi-camadas e multi-segmentados",
  booktitle = "XIX Encontro Nacional de Física de Partículas e Campos",
  year = "2000",
  pdf = "https://www.idiap.ch/~aanjos/papers/enfpc-2000.pdf",
  abstract = "Propõe-se neste trabalho, que a análise conduzida no
  Segundo Nível de Filtragem do Experimento ATLAS, no CERN, seja
  feita por meio de processamento neural sobre a região de interesse
  previamente destacada pelo Primeiro Nível nos Calorímetros. Por
  depender do posicionamento da RoI no detetor, os números de
  camadas, granularides e profundidades das células do calorímetro
  são desconhecidos até o momento da chegada do evento ao sistema de
  análise. Ainda assim, estima-se que o número de células para
  análise estará em torno de 1000 por RoI.  As eficiências de
  separação obtidas, tempos de execução e uma comparação com a
  eficiência de outros métodos empregados para a mesma atividade são
  discutidas.",
}

%%%%%%%%%%%%
%%  1999  %%
%%%%%%%%%%%%

@inproceedings{enfpc-1999,
  author = "André Rabello dos Anjos AND José Manoel de Seixas",
  title = "Integrando Plataformas e Algoritmos para o Segundo Nível
  de Trigger do Experimento ATLAS",
  booktitle = "Encontro Nacional de Física de Partículas e Campos",
  year = "1999",
  pdf = "https://www.idiap.ch/~aanjos/papers/enfpc-1999.pdf",
  abstract = "Este artigo contém um sumário do trabalho realizado no
  âmbito dos estudos de portabilidade da infraestrutura do fluxo de
  dados do Sistema de Filtragem, originalmente escritos em C e
  operando em Sistemas Operacionais comerciais para uma implementação
  orientada a objetos baseada em C++ rodando sobre Linux. Ele discute
  as vantagens deste enfoque, tanto em termos de mantenibilidade
  quanto do custo final de projeto.",
}

%%%%%%%%%%%%
%%  1998  %%
%%%%%%%%%%%%

@inproceedings{enfpc-1998,
  author = "André Rabello dos Anjos AND Augusto Dantas AND José
  Manoel de Seixas",
  title = "Um Protótipo do Sistema de Validação do Nível 2 para as
  Condições do LHC",
  booktitle = "Encontro Nacional de Física de Partículas e Campos",
  year = "1998",
  pages = "32--33",
  pdf = "https://www.idiap.ch/~aanjos/papers/2009/01/09/sbf98.pdf",
  abstract = "O experimento ATLAS pretende comprovar a existência do
  bóson de Higgs. Para tal, um grande sistema de deteção e aquisição
  vem sendo projetado. O sistema aquisição tem a função de separar em
  tempo real interações originárias do decaimento de um Higgs de
  física ordinária. A filtragem de eventos no sistema de aquisição é
  concebida em três níveis, de complexidade crescente e velocidade
  decrescente. O segundo nível pretende utilizar redes de
  computadores pessoais (PC\'s) interconectados por rápidos sistemas
  de rede. A escolha de fabricantes, sistemas operacionais e
  algoritmos de processamento ainda não foi feita, mas esforços em
  prol desta decisão vêm sendo realizados. Neste trabalho
  desenvolve-se uma fração do filtro de segundo nível utilizando-se
  de processamento paralelo, redes neurais artificiais e DSP\'s.",
}

@inproceedings{vecpar-1998,
  author = "J. M. Seixas AND A. R. Anjos AND C. B. Prado AND L. P.
  Calôba AND A. C. H. Dantas and J. C. R. Aguiar",
  title = "Neural classifiers implemented in a transputer based
  parallel machine",
  booktitle = "International Meeting on Vector and Parallel
  Processing (VECPAR)",
  year = "1998",
  pdf = "https://www.idiap.ch/~aanjos/papers/vecpar-1998.pdf",
  abstract = "A transputer based parallel machine is used as a
  development platform for fast neural signal processing applications
  in physics and electricity. The 16 node machine houses 32-bit
  floating point digital signal processors running as coprocessor for
  the transputers, so that signal processing can be optimized. The
  application in physics consists in a prototype of an online
  validation system for a high event rate collider experiment, which
  is implemented using neural networks for physics process
  identification. In electricity, a nonintrusive load monitoring
  system for household appliances is developed using a neural
  discriminator to identify seven groups of equipment.",
}

@article{ieee-tns-1998,
  author = "Seixas, J.M. AND Caloba, L.P. AND Anjos, A.R. AND
  Kastrup, B. AND Dantas, A.C.H. AND Linhares, R.",
  title = "A neural online triggering system based on parallel processing",
  journal = "IEEE Transactions on Nuclear Science",
  year = "1998",
  month = 8,
  volume = "45",
  number = "4",
  pages = "1814--1818",
  pdf = "https://www.idiap.ch/~aanjos/papers/ieee-tns-1998.pdf",
  abstract = "The study of a prototype of the second-level triggering
  system for operation at LHC conditions is addressed by means of a
  parallel machine implementation. The 16 node transputer based
  machine uses a fast digital signal processor acting as a
  coprocessor for optimizing signal processing applications. A
  C-language development environment is used for running all
  applications at ultimate speed. The implementation is based on
  information supplied by four detectors and includes two phases of
  system operation: feature extraction and global decision. Feature
  extraction for calorimeters and global decision processing are
  performed by means of neural networks. Preprocessing and neural
  network parameters rest in memory and the activation function is
  implemented using a look up table. Simulated data for the
  second-level trigger operation are used for performance evaluation.",
}

%%%%%%%%%%%%
%%  1997  %%
%%%%%%%%%%%%

@phdthesis{grad-thesis-1997,
  author = "André Rabello dos Anjos",
  title = "Sistema de classificação baseado em uma máquina com
  sistema distribuído",
  school = "Departamento de Eletronica/UFRJ",
  year = "1997",
  pdf = "https://www.idiap.ch/~aanjos/papers/grad-thesis-1997.pdf",
  abstract = "Na busca de novos canais físicos em experimentos com
  partículas colididas, sistemas de validação têm se mostrado de
  grande valia. Normalmente os subprodutos de colisões
  interparticulares representam física ordinária e conhecida enquanto
  que nova física aparece camuflada neste meio. A impossibilidade de
  gravação e análise do imenso volume de dados produzido nestes
  ambientes exige o uso de sistemas de validação para que se maximize
  o espaço de gravação e se minimize o espaço de procura de novos fenômenos.

  Em particular, no CERN, o par acelerador/colisionador do LHC, que
  estará operacional no ano de 2005, utilizará um destes sistemas de
  validação baseado em 3 níveis em cascata de complexidade crescente
  e velocidade decrescente. Este sistema tem por objetivo a análise e
  filtragem, em tempo real, de um volume de dados cuja taxa chega à
  impressionante faixa de 100.000.000 por segundo.

  A divisão do sistema em 3 etapas distintas visa produzir um sistema
  de validação o mais eficiente e dinâmico possível, sem que se
  sobrecarregue nenhuma das partes. Para o primeiro nível estima-se a
  utilização de processadores velozes, com nível baixo de
  programação, capazes de suportar a taxa inicial dos eventos. Para o
  terceiro nível o uso de pesado ambiente computacional é previsto.

  No segundo nível ambientes altamente programáveis serão combinados
  com técnicas de paralelização de aplicações para que atinjamos a
  taxa de processamento requerida de 100.000 eventos por segundo.

  Vários tipos de tecnologia estão sendo testadas em todo o mundo
  para que se decida, não somente sobre a arquitetura, mas, também,
  sobre o tipo de equipamento a ser empregado neste extenso sistema
  de classificação.

  Este trabalho é sobre a implementação em uma máquina com
  processamento distribuído de uma das arquiteturas previstas para o
  segundo nível de validação (ou classificação) do experimento
  ATLAS/LHC. A  máquina em questão é um sistema Telmat TN310 com
  processamento distribuído por 16 nós padrão HTRAM totalmente
  conectados através de uma rede de chaves assíncronas. A arquitetura
  mencionada prevê a utilização de técnicas de paralelismo de dados e
  fluxo na obtenção de menores tempos de processamento.

  O objetivo final é entender se o processamento em sistemas
  semelhantes a uma TN310 (visamos o tipo de nó-de-processamento e o
  padrão de conexão entre estes) pode ser viável para o segundo nível
  de validação. Isto se dará através da análise e capacidade de
  abstração proporcionadas pelo desenvolvimento da aplicação sugerida
  no equipamento.

  Soma-se ao trabalho o desenvolvimento de uma unidade de decisões
  globais baseado em redes neurais. A unidade constitui processo
  central do sistema de validação. Resultados atingidos são expostos
  e discussões sobre técnicas de implementação são realizadas no
  decorrer da documentação.",
}

@inproceedings{icspat-1997,
  author = "Seixas, J.M. AND Calôba, L.P. AND Anjos, A.R. AND Dantas,
  A.C.H. AND Linhares, R.",
  title = "Fast Neural Decision System Based On DSPs And Parallel Processing",
  booktitle = "International Conference on Signal Processing
  Applications and Technologies, San Diego, USA",
  year = "1997",
  pages = "1629--1633",
  pdf = "https://www.idiap.ch/~aanjos/papers/icspat-1997.pdf",
  abstract = "A prototype of an online event validation system is
  developed for application in a high-energy collider experiment. The
  system mainly uses neural networks for extracting rate events with
  physics significance from a huge background noise. It is based on
  processing the information collected from different detectors
  placed around the collision point. Combining a feature extraction
  phase for each detector with a global decision phase for final
  decision on discarding or not a given event, the system acts on
  events previously selected by a first-level analysis that reduces
  the event rate to 100 kHz. To cope with this input frequency, the
  proposed system is being emulated in a 16 node transputer base
  parallel machine that has a fast digital signal processor running
  as a co-procesor for each node.",
}

%%%%%%%%%%%%
%%  1996  %%
%%%%%%%%%%%%

@inproceedings{cba-1996,
  author = "Seixas, J.M. AND Calôba, L.P. AND Anjos, A.R.",
  title = "Particle discrimination using sub-optimal filtering techniques",
  booktitle = "Congresso Brasileiro de Automatica (CBA), São Paulo, Brasil",
  year = "1996",
  pages = "635--640",
  pdf = "https://www.idiap.ch/~aanjos/papers/cba-1996.pdf",
  abstract = "The discrimination of high energy electrons and pions
  using a scintillating fiber calorimeter is addressed. The
  discrimination method is based on analyzing the time structure of
  calorimeter signals and achieves discrimination response smaller
  than 100 ns. Signals pass through a high performance constant
  fraction discriminator and events that lie in the confusion region
  of this discriminator are analyzed through a sub-optimal filltering
  technique based on pulse integration. The composed discrimination
  system achieves 98\% electron eficiency with less than 0.1\% of
  pions being misclassified as electrons.",
}