Robust Noisy-Label Learning: A Novel Class-Specific Autoencoder-Guided Sample Selection Framework
Deep learning has been extensively applied to sample selection. However, the performance of deep learning-based sample selection methods can be substantially degraded when training data are contaminated by noisy labels, a common issue in practical industrial settings. To address this challenge, this paper proposes Clas...