Adaptive Asynchronous Split Federated Learning for Medical Image Segmentation

Adaptive Asynchronous Split Federated Learning for Medical Image Segmentation

Split federated (SplitFed) learning offers promise for collaborative machine learning across decentralized and resource-constrained clients (edge devices, nodes, or organizations) in various applications, including healthcare. However, real-world challenges arise in heterogeneous environments where...

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Bibliographic Details
Main Authors: Chamani Shiranthika, Hadi Hadizadeh, Parvaneh Saeedi, V. Ivan Bajic
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Adaptive training
asynchronous training
medical image segmentation
split federated learning
Online Access:https://ieeexplore.ieee.org/document/10776986/
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