G-T correcting: an improved training of image segmentation under noisy labels
Author:
Funder
Science and Technology Commission of Shanghai Municipality
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11517-024-03170-4.pdf
Reference33 articles.
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4. Liu S, Niles-Weed J, Razavian N, Fernandez-Granda C (2020) Early-learning regularization prevents memorization of noisy labels. In: Proc Adv Neural Inf Process Syst 20331–20342. https://doi.org/10.48550/arXiv.2007.00151
5. Han B, Yao Q, Yu X, et al (2018) Co-teaching: robust training of deep neural networks with extremely noisy labels. In: Proc Int Conf Neural Inf Process Syst 8536–8546. https://doi.org/10.48550/arXiv.1804.06872
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