1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CV2023
BroadCAM: Outcome-agnostic Class Activation Mapping for Small-scale Weakly Supervised Applications
Jiatai Lin, Guoqiang Han, Xuemiao Xu +5
Class activation mapping~(CAM), a visualization technique for interpreting deep learning models, is now commonly used for weakly supervised semantic segmentation~(WSSS) and object…
cs.CV2023★ 1 cited
Rethinking Mitosis Detection: Towards Diverse Data and Feature Representation
Hao Wang, Jiatai Lin, Danyi Li +11
Mitosis detection is one of the fundamental tasks in computational pathology, which is extremely challenging due to the heterogeneity of mitotic cell. Most of the current studies s…
eess.IV2023
FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification
Tianpeng Deng, Yanqi Huang, Guoqiang Han +7
Histopathological tissue classification is a fundamental task in computational pathology. Deep learning-based models have achieved superior performance but centralized training wit…