Mastering Domain Generalization in Remote Sensing


 Mastering Domain Generalization in Remote Sensing focuses on building robust learning models that maintain high performance across diverse sensors, regions, and environmental conditions. By leveraging vision foundation models, advanced feature alignment, and domain-invariant representations, this approach minimizes domain shift in remote sensing analysis. It enables scalable and reliable applications in land cover mapping, change detection, and environmental monitoring without heavy dependence on target-domain labels.

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