2 papers
cs.CV2025
FedDEAP: Adaptive Dual-Prompt Tuning for Multi-Domain Federated Learning
Yubin Zheng, Pak-Hei Yeung, Jing Xia +4
Federated learning (FL) enables multiple clients to collaboratively train machine learning models without exposing local data, balancing performance and privacy. However, domain sh…
eess.IV2025
Bridging the Inter-Domain Gap through Low-Level Features for Cross-Modal Medical Image Segmentation
Pengfei Lyu, Pak-Hei Yeung, Xiaosheng Yu +4
This paper addresses the task of cross-modal medical image segmentation by exploring unsupervised domain adaptation (UDA) approaches. We propose a model-agnostic UDA framework, Low…