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Session of Machine Learning Division of CyberLabs

Conducted on: 17/10/2025

Agenda

Masked RCNN, YOLOv1, YOLOv2

Summary

  1. How RoIAlign preserves exact spatial locations through bilinear interpolation.
  2. Advantage of Decoupling
  3. ⁠How Multi Task Learning allows model to focus on spatial layout?
  4. Brief overview of techniques such as Feature Pyramid Networks (FPN), Data Distillation for unlabeled data
  5. Reframing object detection as a single regression problem
  6. ⁠Intuition behind YOLO working better at capturing global context than RCNNs
  7. Mathematical intuition behind Multi-part loss function of YOLO
  8. ⁠Analysis of systemic improvements in YOLOv2 like introduction of anchor boxes to improve recall

Agenda for the next session

  • SimCLR V1
  • SimCLR V2

Report Compiled by

Ayushman Dutta

Attendees

Third Year Attendees: Mukil M Sir, Harshvardhan Saini Sir, Dilshad Sir, Green Sir

Second Year Attendees: Anab, Arnav, Ritesh, Rajat, Arjav, Abhishek, Ayushman, Sreenandan, Anukul

Absentees

Second Year: None