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FedMAD: Modulation-Aware Directional Aggregation for Federated Learning in Remote Sensing Image Classification
Federated learning (FL) has recently attracted increasing attention in remote sensing (RS) since it enables collaborative model training across decentralized RS image archives without requiring direct access to local data. However, FL performance significantly degrades when the data distributions be
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