2 papers
cs.CV2024
Enhancing Weakly-Supervised Histopathology Image Segmentation with Knowledge Distillation on MIL-Based Pseudo-Labels
Yinsheng He, Xingyu Li, Roger J. Zemp
Segmenting tumors in histological images is vital for cancer diagnosis. While fully supervised models excel with pixel-level annotations, creating such annotations is labor-intensi…
eess.IV2024
BMAD: Benchmarks for Medical Anomaly Detection
Jinan Bao, Hanshi Sun, Hanqiu Deng +3
Anomaly detection (AD) is a fundamental research problem in machine learning and computer vision, with practical applications in industrial inspection, video surveillance, and medi…