Federated Coupled Contrastive Learning on Remote Sensing Image Classification (opens in new tab)

Classification for remote sensing (RS) images plays a crucial role in various fields such as disaster assessment and urban planning. Nevertheless, due to resource limitations and privacy issues, directly transferring data to the ground for high-performance centralized training is often impractical. Federated learning (FL) has emerged as a revolutionary distributed learning paradigm, which enables collaborative training of a model without data sharing. However, since the RS data is distributed...