4 papers
Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges
Yuan Zhang, Xinfeng Zhang, Xiaoming Qi +4
Content generation modeling has emerged as a promising direction in computational pathology, offering capabilities such as data-efficient learning, synthetic data augmentation, and…
Spatio-Temporal Representation Decoupling and Enhancement for Federated Instrument Segmentation in Surgical Videos
Zheng Fang, Xiaoming Qi, Chun-Mei Feng +3
Surgical instrument segmentation under Federated Learning (FL) is a promising direction, which enables multiple surgical sites to collaboratively train the model without centralizi…
Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for Federated Continual Learning
Xiaoming Qi, Jingyang Zhang, Huazhu Fu +3
Federated continual learning (FCL) offers an emerging pattern to facilitate the applicability of federated learning (FL) in real-world scenarios, where tasks evolve dynamically and…
Dynamic Allocation Hypernetwork with Adaptive Model Recalibration for FCL
Xiaoming Qi, Jingyang Zhang, Huazhu Fu +3
Federated continual learning (FCL) offers an emerging pattern to facilitate the applicability of federated learning (FL) in real-world scenarios, where tasks evolve dynamically and…