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Energy-Efficient Hierarchical Federated Anomaly Detection for the Internet of Underwater Things via Selective Cooperative Aggregation

Fuente: arXiv

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Détails bibliographiques
Auteurs principaux:	Omeke, Kenechi, Mollel, Michael, Zhang, Lei, Abbasi, Qammer H., Imran, Muhammad Ali
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

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