3 accepted papers
Whole Slide Image (WSI) classification has been widely used in pathological diagnosis and prognosis prediction, and it is commonly formulated as a weakly-supervised Multiple Instance Learning (MIL) problem because of the large size of WSIs and the difficulty of obtaining fine-grained annotations. In…
Weakly supervised semantic segmentation (WSSS) with image-level labels aims to achieve segmentation tasks without dense annotations. However attributed to the frequent coupling of co-occurring objects and the limited supervision from image-level labels the challenging co-occurrence problem is widely…
Bag-based multiple instance learning (MIL) methods have become the mainstream for Whole Slide Image (WSI) classification. However, there are still three important issues that have not been fully addressed: (1) positive bags with a low positive instance ratio are prone to the influence of a large num…