Remote sensing foundation models are increasingly used for downstream tasks, but their behavior under extreme class imbalance is not well characterized. We present an empirical study of pretrained encoders for SAR ship classification on two public datasets, FUSARShip and OpenSARShip, which exhibit severe label skew. We...
Ch Muhammad Awais, M. Reggiannini, Davide Moroni· International Conference on...· 0 citations
Six pretrained models on two SAR ship datasets are evaluated in in-domain classification, cross-dataset transfer, and unknown-class detection, showing that cross-dataset generalization in SAR remains limited and that task-specific uncertainty scores are often more informative than MC-dropout variance for held-out-class...
Ch Muhammad Awais, M. Reggiannini, Davide Moroni et al.· 0 citations
Remote-sensing foundation models offer strong representations for SAR imagery, but their behavior under severe long-tail class imbalance is still not well characterized, so four oversampling methods in embedding space exclusively to minority classes are applied and a lightweight classifier head is trained on the augmen...
Ch Muhammad Awais, M. Reggiannini, Davide Moroni· 0 citations
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