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.
On the opportunities and risks of foundation models
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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.