Vector quantization induces a structured partition of the representation space for composing heterogeneous multiclass calibration maps via shared codeword-dependent Dirichlet factors.
Medmnist v2-a large-scale lightweight benchmark for 2d and 3d biomedical image classification.Scientific Data, 10(1):41
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Global color moments and RGB/HSV histograms alone support binary benign-malignant classification at up to 89% accuracy with classical ML classifiers, substantially above random baselines.
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Divide et Calibra: Multiclass Local Calibration via Vector Quantization
Vector quantization induces a structured partition of the representation space for composing heterogeneous multiclass calibration maps via shared codeword-dependent Dirichlet factors.
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Beyond Morphology: Quantifying the Diagnostic Power of Color Features in Cancer Classification
Global color moments and RGB/HSV histograms alone support binary benign-malignant classification at up to 89% accuracy with classical ML classifiers, substantially above random baselines.