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papersSEP 11 04:00 UTC

arXiv Paper Proposes Classifier Reconstruction to Predict Synthetic Data Utility

A new arXiv preprint examines how well synthetic images help binary classification tasks where positive examples are scarce, as in medical imaging and industrial inspection. The authors propose measuring a "discriminative span" and reconstructing a classifier to predict how useful generated samples will be. The work aims to guide synthetic data selection in severely imbalanced settings.

arXivclass imbalancedata selectionindustrial-inspectionmedical imagingsynthetic data

COVERAGE · 1 REPORT · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.LGDiscriminative Span as a Predictor of Synthetic Data Utility via Classifier Reconstruction ↗SEP 11 04:00 UTC

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