3 papers
eess.IV2026
SplitFed-CL: A Split Federated Co-Learning Framework for Medical Image Segmentation with Inaccurate Labels
Zahra Hafezi Kafshgari, Hadi Hadizadeh, Parvaneh Saeedi
Split Federated Learning (SplitFed) combines federated and split learning to preserve privacy while reducing client-side computation. However, in medical image segmentation, hetero…
cs.CV2026
Smart Split-Federated Learning over Noisy Channels for Embryo Image Segmentation
Zahra Hafezi Kafshgari, Ivan V. Bajic, Parvaneh Saeedi
Split-Federated (SplitFed) learning is an extension of federated learning that places minimal requirements on the clients computing infrastructure, since only a small portion of th…
eess.IV2025
MedSegNet10: A Publicly Accessible Network Repository for Split Federated Medical Image Segmentation
Chamani Shiranthika, Zahra Hafezi Kafshgari, Hadi Hadizadeh +1
Machine Learning (ML) and Deep Learning (DL) have shown significant promise in healthcare, particularly in medical image segmentation, which is crucial for accurate disease diagnos…