A unified framework for training deep neural networks with better generalization via self-ensemble label correction.

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Title: A unified framework for training deep neural networks with better generalization via self-ensemble label correction.
Authors: Xia, Yuelong1,2,3, xyl@ynnu.edu.cn, Liu, Wenjie1, Sun, Xiaodi1, Yang, Jing1, Tong, Yihang1, Zhang, Yungang1
Source: Artificial Intelligence Review; Apr2026, Vol. 59 Issue 4, p1-38, 38p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
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  Data: A unified framework for training deep neural networks with better generalization via self-ensemble label correction.
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  Data: <searchLink fieldCode="AU" term="%22Xia%2C+Yuelong%22">Xia, Yuelong</searchLink><relatesTo>1,2,3</relatesTo>, <i>xyl@ynnu.edu.cn</i><br /><searchLink fieldCode="AU" term="%22Liu%2C+Wenjie%22">Liu, Wenjie</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Sun%2C+Xiaodi%22">Sun, Xiaodi</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Yang%2C+Jing%22">Yang, Jing</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Tong%2C+Yihang%22">Tong, Yihang</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Zhang%2C+Yungang%22">Zhang, Yungang</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Artificial+Intelligence+Review%22">Artificial Intelligence Review</searchLink>; Apr2026, Vol. 59 Issue 4, p1-38, 38p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=192427988
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s10462-026-11523-8
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      – Code: eng
        Text: English
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        PageCount: 38
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      – TitleFull: A unified framework for training deep neural networks with better generalization via self-ensemble label correction.
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            NameFull: Xia, Yuelong
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            NameFull: Liu, Wenjie
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            NameFull: Sun, Xiaodi
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            NameFull: Yang, Jing
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            NameFull: Tong, Yihang
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            – D: 01
              M: 04
              Text: Apr2026
              Type: published
              Y: 2026
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              Value: 59
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