A Faster R-CNN plus classifier ensemble achieved high recall (0.95) but low precision (0.13) on MIDOG 2025, and no optimization variant recovered the loss.
RandStainNA: Learning Stain- Agnostic Features from Histology Slides by Bridging Stain Augmentation and Normaliza- tion, page 212–221
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Challenges and Lessons from MIDOG 2025: A Two-Stage Approach to Domain-Robust Mitotic Figure Detection
A Faster R-CNN plus classifier ensemble achieved high recall (0.95) but low precision (0.13) on MIDOG 2025, and no optimization variant recovered the loss.