1 citations · 1 across the 3 of their papers we have counts for
4 papers
MUSE: Harnessing Precise and Diverse Semantics for Few-Shot Whole Slide Image Classification
Jiahao Xu, Sheng Huang, Xin Zhang +3
In computational pathology, few-shot whole slide image classification is primarily driven by the extreme scarcity of expert-labeled slides. Recent vision-language methods incorpora…
Dual-View Alignment Learning with Hierarchical-Prompt for Class-Imbalance Multi-Label Classification
Sheng Huang, Jiexuan Yan, Beiyan Liu +2
Real-world datasets often exhibit class imbalance across multiple categories, manifesting as long-tailed distributions and few-shot scenarios. This is especially challenging in Cla…
Multiple Instance Learning Framework with Masked Hard Instance Mining for Gigapixel Histopathology Image Analysis
Wenhao Tang, Sheng Huang, Heng Fang +3
Digitizing pathological images into gigapixel Whole Slide Images (WSIs) has opened new avenues for Computational Pathology (CPath). As positive tissue comprises only a small fracti…
Communication-Efficient and Personalized Federated Foundation Model Fine-Tuning via Tri-Matrix Adaptation
Yongle Li, Bo Liu, Sheng Huang +3
In federated learning, fine-tuning pre-trained foundation models poses significant challenges, particularly regarding high communication cost and suboptimal model performance due t…