FedFusion: Manifold-Driven Federated Learning for Multi-Satellite and Multi-Modality Fusion
Author:
Affiliation:
1. State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an, China
2. College of Electrical and Information Engineering, Hunan University, Changsha, China
Funder
National Natural Science Foundation of China
Young Elite Scientist Sponsorship Program by the China Association for Science and Technology
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10354519/10342879.pdf?arnumber=10342879
Reference48 articles.
1. Proof-of-Concept of a Federated Satellite System Between Two 6-Unit CubeSats for Distributed Earth Observation Satellite Systems
2. Ultra-Dense LEO Satellite Constellations: How Many LEO Satellites Do We Need?
3. Using publicly available satellite imagery and deep learning to understand economic well-being in Africa
4. Deep learning and data fusion to estimate surface soil moisture from multi-sensor satellite images
5. Coming Down to Earth: Satellite-to-Street View Synthesis for Geo-Localization
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