Learning from open-set noisy labels based on multi-prototype modeling
Author:
Funder
National Key Research and Development Program of China
Ministry of Science and Technology of the People's Republic of China
National Natural Science Foundation of China
Publisher
Elsevier BV
Reference40 articles.
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4. Y. Yao, Z. Sun, C. Zhang, F. Shen, Q. Wu, J. Zhang, Z. Tang, Jo-src: A contrastive approach for combating noisy labels, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021, pp. 5192–5201.
5. Z. Sun, F. Shen, D. Huang, Q. Wang, X. Shu, Y. Yao, J. Tang, Pnp: Robust learning from noisy labels by probabilistic noise prediction, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022, pp. 5311–5320.
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