Enhancing Continual Noisy Label Learning with�Uncertainty-Based Sample Selection and�Feature Enhancement
The task of continual learning is to design algorithms that can address the problem of catastrophic forgetting. However, in the real world, there are noisy labels due to inaccurate human annotations and other factors, which seem to exacerbate catastrophic forgetting. To tackle both catastrophic forg...
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Springer Science and Business Media Deutschland GmbH
2025
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