5 citations · 11 across the 11 of their papers we have counts for
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cs.CV2025
Partially Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation
Lei Zhu, Yanyu Xu, Huazhu Fu +3
Unpaired Multi-Modal Learning (UMML) which leverages unpaired multi-modal data to boost model performance on each individual modality has attracted a lot of research interests in m…
cs.CV2024★ 2 cited
An Aggregation-Free Federated Learning for Tackling Data Heterogeneity
Yuan Wang, Huazhu Fu, Renuga Kanagavelu +3
The performance of Federated Learning (FL) hinges on the effectiveness of utilizing knowledge from distributed datasets. Traditional FL methods adopt an aggregate-then-adapt framew…
cs.CV2024★ 2 cited
Uncertainty-aware Medical Diagnostic Phrase Identification and Grounding
Ke Zou, Yang Bai, Bo Liu +9
Medical phrase grounding is crucial for identifying relevant regions in medical images based on phrase queries, facilitating accurate image analysis and diagnosis. However, current…