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arXiv AI By Anabik Pal, Ganesh Patidar, Bikash Santra

FedDermaSeg: Federated Learning for Dermatological Image Segmentation

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FedDermaSeg explores federated learning for skin lesion segmentation, aiming to preserve privacy by avoiding centralized data aggregation. Using the ISIC 2018 dataset in a simulated distributed setting, the federated model matches centralized training performance and outperforms locally trained models. The study demonstrates that collaborative, privacy‑preserving segmentation is feasible without central image storage.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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