Bin-wise temperature scaling, applied to per-confidence bins and supplemented by augmented validation samples, reduces expected calibration error relative to temperature scaling across tested image classifiers.
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Bin-wise Temperature Scaling (BTS): Improvement in Confidence Calibration Performance through Simple Scaling Techniques
Bin-wise temperature scaling, applied to per-confidence bins and supplemented by augmented validation samples, reduces expected calibration error relative to temperature scaling across tested image classifiers.