Federated Deep Learning With Prototype Matching for Object Extraction From Very-High-Resolution Remote Sensing Images
Published in IEEE Transactions on Geoscience and Remote Sensing, 2023
This paper proposes a novel federated learning scheme with prototype matching (FedPM) to collaboratively learn a richer DCNN model by leveraging remote sensing data distributed among multiple clients.
Recommended citation: Zhang, X., Zhang, B., Yu, W. and Kang, X., 2023. Federated Deep Learning With Prototype Matching for Object Extraction From Very-High-Resolution Remote Sensing Images. IEEE Transactions on Geoscience and Remote Sensing, 61, pp.1-16.