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Impact of Data Augmentation on Confidence Calibration in Melanoma Classification
artificial-intelligencecomputer-vision-and-pattern-recognitionlogic-in-computer-sciencemachine-learning
Accurately quantifying the predictive uncertainty or improving model calibration plays an important role in medical image classification, in particular in melanoma diagnosis, where accurate uncertainty quantification can have significant implications for patient care. One of the methods for calibrat
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