9 citations · 14 across the 4 of their papers we have counts for
4 papers
Multiple Instance Learning Framework with Masked Hard Instance Mining for Whole Slide Image Classification
Wenhao Tang, Sheng Huang, Xiaoxian Zhang +3
The whole slide image (WSI) classification is often formulated as a multiple instance learning (MIL) problem. Since the positive tissue is only a small fraction of the gigapixel WS…
High-level semantic feature matters few-shot unsupervised domain adaptation
Lei Yu, Wanqi Yang, Shengqi Huang +2
In few-shot unsupervised domain adaptation (FS-UDA), most existing methods followed the few-shot learning (FSL) methods to leverage the low-level local features (learned from conve…
Boosting Multi-Label Image Classification with Complementary Parallel Self-Distillation
Jiazhi Xu, Sheng Huang, Fengtao Zhou +3
Multi-Label Image Classification (MLIC) approaches usually exploit label correlations to achieve good performance. However, emphasizing correlation like co-occurrence may overlook…
Few-shot Unsupervised Domain Adaptation with Image-to-class Sparse Similarity Encoding
Shengqi Huang, Wanqi Yang, Lei Wang +2
This paper investigates a valuable setting called few-shot unsupervised domain adaptation (FS-UDA), which has not been sufficiently studied in the literature. In this setting, the…