Federated Learning Across Decentralized and Unshared Archives for Remote Sensing Image Classification

no code implementations • 10 Nov 2023 • Barış Büyüktaş, Gencer Sumbul, Begüm Demir

After presenting an extensive overview of the selected algorithms, a theoretical comparison of the algorithms is conducted based on their: 1) local training complexity; 2) aggregation complexity; 3) learning efficiency; 4) communication cost; and 5) scalability in terms of number of clients.

Federated Learning Multi-Label Classification +2

Learning Across Decentralized Multi-Modal Remote Sensing Archives with Federated Learning

no code implementations • 1 Jun 2023 • Barış Büyüktaş, Gencer Sumbul, Begüm Demir

The MF module performs iterative model averaging to learn without accessing data on clients in the case that clients are associated with different data modalities.

Federated Learning Image Classification