Abstract: Few-Shot Class-Incremental Learning (FSCIL) faces a huge stability-plasticity challenge due to continuously learning knowledge from new classes with a small number of training samples ...
Abstract: Confidence calibration in classification models is a vital technique for accurately estimating the posterior probabilities of predicted results, which is crucial for assessing the likelihood ...
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