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Typicality- and instance-dependent label noise-combating: a novel framework for simulating and combating real-world noisy labels for endoscopic polyp classification

Crossref DOI link: https://doi.org/10.1186/s42492-024-00162-x

Published Online: 2024-05-06

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Gao, Yun

Fu, Junhu

Wang, Yuanyuan

Guo, Yi
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (62371139)

Science and Technology Commission of Shanghai Municipality (22ZR1404800, 22DZ1100101)
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Text and Data Mining valid from 2024-05-06

Version of Record valid from 2024-05-06
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Article History

Received: 29 December 2023

Accepted: 14 April 2024

First Online: 6 May 2024

Declarations

:

: The authors declare that they have no competing interests.

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