NASA A.42: machine learning for ACCESS #6
Description
NASA RFP A.42: Machine Learning for ACCESS
NSPIRES - Solicitations Summary: Advancing Collaborative Connections for Earth System Science
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The Earth Science Data System (ESDS) Program is soliciting proposals for Advancing Collaborative Connections for Earth System Science (ACCESS).
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The focus of this solicitation is to help EOSDIS address data management, discoverability, and utilization challenges faced by users and curators of NASA’s Earth science data. Although focused on information technology development and deployment, the ACCESS program is targeted at addressing existing and anticipated future needs of the research and applied science communities. Proposal teams must include both information technology and Earth science expertise, and must be tied directly to specific issues facing Earth science and applied science users interacting with EOSDIS.
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NASA is seeking proposals that significantly advance discovery, management, use and analysis of large and complex Earth science data sets from EOSDIS.
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2.1.1. Machine Learning
NASA seeks innovative and practical applications of Machine Learning (ML) to improve discovery, categorization and event detection from EOSDIS’s data, imagery and/or metadata. Proposers should identify use cases that support NASA’s Earth Science research objectives or demonstrate how the proposed ML approach will improve access to NASA’s near-real-time or standard science data products (https://earthdata.nasa.gov/community/community-data-system-programs/access-projects/ACCESS17). Proposals in this area must identify training data, a trained classifier, testing protocol, and a final software application. -
Notices of intent are requested by December 1, 2017, and proposals are due January 31, 2018.
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See: #5: Explore Deep Learning (TensorFlow) + Google Earth Engine
Check out robust tools that are part of EOSDIS:
