4 citations · 12 across the 6 of their papers we have counts for
6 papers
Benchmarking Real-World Medical Image Classification with Noisy Labels: Challenges, Practice, and Outlook
Yuan Ma, Junlin Hou, Chao Zhang +4
Learning from noisy labels remains a major challenge in medical image analysis, where annotation demands expert knowledge and substantial inter-observer variability often leads to…
Delving into Out-of-Distribution Detection with Medical Vision-Language Models
Lie Ju, Sijin Zhou, Yukun Zhou +4
Recent advances in medical vision-language models (VLMs) demonstrate impressive performance in image classification tasks, driven by their strong zero-shot generalization capabilit…
Diversified and Personalized Multi-rater Medical Image Segmentation
Yicheng Wu, Xiangde Luo, Zhe Xu +5
Annotation ambiguity due to inherent data uncertainties such as blurred boundaries in medical scans and different observer expertise and preferences has become a major obstacle for…
HGCLIP: Exploring Vision-Language Models with Graph Representations for Hierarchical Understanding
Peng Xia, Xingtong Yu, Ming Hu +4
Object categories are typically organized into a multi-granularity taxonomic hierarchy. When classifying categories at different hierarchy levels, traditional uni-modal approaches…
NurViD: A Large Expert-Level Video Database for Nursing Procedure Activity Understanding
Ming Hu, Lin Wang, Siyuan Yan +7
The application of deep learning to nursing procedure activity understanding has the potential to greatly enhance the quality and safety of nurse-patient interactions. By utilizing…
Privacy-preserving Early Detection of Epileptic Seizures in Videos
Deval Mehta, Shobi Sivathamboo, Hugh Simpson +3
In this work, we contribute towards the development of video-based epileptic seizure classification by introducing a novel framework (SETR-PKD), which could achieve privacy-preserv…