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cs.CV2025
Divide, Conquer and Unite: Hierarchical Style-Recalibrated Prototype Alignment for Federated Medical Segmentation
Xingyue Zhao, Wenke Huang, Xingguang Wang +5
Federated learning enables multiple medical institutions to train a global model without sharing data, yet feature heterogeneity from diverse scanners or protocols remains a major…
cs.CV2023
Asymmetric Co-Training with Explainable Cell Graph Ensembling for Histopathological Image Classification
Ziqi Yang, Zhongyu Li, Chen Liu +7
Convolutional neural networks excel in histopathological image classification, yet their pixel-level focus hampers explainability. Conversely, emerging graph convolutional networks…