… In this article, we propose a novel adaptive learning scheme of SegmentedFederated
Learning (Segmented-FL) (Fig. 1). We employ periodic local model evaluation and segmentation …

… data and diversity of their LANs, a segmented federated learning is proposed in this research,
… consists of two main parts: intrusion detection in LANs and segmented federated learning. …

… It is of great challenges for conventional federated learning approaches to efficiently utilize
… federated learning to tackle this problem. In particular, we propose a segmented gossip …

… learning approach of Segmented-Federated Learning (SegmentedFL) for better learning from
… We employ periodic local model evaluation and segmentation for adaptive model training. …

… -time platform to support network and federated learning functions integration, validating the
… , focusing in particular on brain tumor segmentation. To demonstrate the system in a real …

… We also proposed a survey of federated learning methodologies to enhance global segmentation
performance … This paper focuses on the issues of federated learning in segmentation. …

… This study introduced SegViz, a federated learning framework that achieves excellent
multi-organ segmentation performance by effectively aggregating knowledge from unique …

… federated learning framework. The model sensitivity to vertebral body pixels and segmentation
… performance of vertebral body segmentation models is boosted by the global federated …

… Segmentation enhanced Asynchronous Federated Learning (AS-AFL) model, aiming to
improve the learning … Specifically, a meta-learning based adaptive segmentation scheme is …

… To tackle the aforementioned challenges, we propose a Fed-UDS (Unseen Domain
Segmentation Network Based on Federated Learning) method that enhances the performance of …