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rare species are underrepresented due to their natural occurrence and sampling bias, leading to substantial class imbalance.
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The reported 86.3% top-1 / 98.8% top-5 accuracy aggregates all 95 classes, masking the rare-species long tail—often the most informative for biodiversity monitoring. Per-class performance matters for operational ecology. We extend the classifier by adding multi-scale scattering features to CNN softmax outputs to test whether rare-class performance can improve without degrading overall accuracy.
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Anne Fouilloux
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Paper annotation: rare species are underrepresented due to their natural occurrence and sampling bias, leading to substantial class imbalance.
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