Yong Cheng

CLIP-Guided Adaptive Sample Selection with Machine Unlearning and Negative Learning Strategies for Noisy Labels Learning

Deep neural networks (DNNs), due to their over-parameterization and memorization capacity, are prone to fitting incorrect labels in training data, which can substantially degrade their performance. Consequently, LNL has attracted increasing attention. Popular LNL methods select potentially clean samples for reliable su...