DGR-MIL: Exploring Diverse Global Representation in Multiple Instance
Learning for Whole Slide Image Classification
DGR-MIL: Exploring Diverse Global Representation in Multiple Instance
Learning for Whole Slide Image Classification
Multiple instance learning (MIL) stands as a powerful approach in weakly supervised learning, regularly employed in histological whole slide image (WSI) classification for detecting tumorous lesions. However, existing mainstream MIL methods focus on modeling correlation between instances while overlooking the inherent diversity among instances. However, few MIL methods have aimed …