CroSatFL cuts ground station communications by over 100x and transmission energy by 6x in satellite federated learning compared to baselines, while keeping competitive accuracy.
Eurosat: A novel dataset and deep learning benchmark for land use and land cover classi- fication
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
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2026 2verdicts
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A hybrid CNN-ViT foundation model trained only on Dutch high-resolution imagery with temporal inputs achieves competitive results on global remote sensing benchmarks despite using fewer parameters and less pretraining data than larger state-of-the-art models.
citing papers explorer
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CroSatFL: Energy-Efficient Federated Learning with Cross-Aggregation for Satellite Edge Computing
CroSatFL cuts ground station communications by over 100x and transmission energy by 6x in satellite federated learning compared to baselines, while keeping competitive accuracy.
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Developing a foundation model for high-resolution remote sensing data of the Netherlands
A hybrid CNN-ViT foundation model trained only on Dutch high-resolution imagery with temporal inputs achieves competitive results on global remote sensing benchmarks despite using fewer parameters and less pretraining data than larger state-of-the-art models.