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Discriminative Span as a Predictor of Synthetic Data Utility via Classifier Reconstruction
In many real-world computer vision applications, including medical imaging and industrial inspection, binary classification tasks are characterized by a severe scarcity of positive samples. A widely adopted solution is to generate synthetic positive data using image-to-image transformations applied
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