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1 Ergebnisse
1
ACE: A Coarse-to-Fine Learning Framework for Reliable Repre..:
, In:
2022 International Joint Conference on Neural Networks (IJCNN)
,
Zhang, Chenbin
;
Yang, Xiangli
;
Liang, Jian
... - p. 1-8 , 2022
Link:
https://doi.org/10.1109/IJCNN55064.2022.9892045
RT T1 <cTitle>2022 International Joint Conference on Neural Networks (IJCNN)</cTitle>: T1 <Title>ACE: A Coarse-to-Fine Learning Framework for Reliable Representation Learning Against Label Noise</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9892045&Exemplar=1&LAN=DE A1 Zhang, Chenbin A1 Yang, Xiangli A1 Liang, Jian A1 Bai, Bing A1 Bai, Kun A1 King, Irwin A1 Xu, Zenglin YR 2022 SN 2161-4407 K1 Representation learning K1 Geometry K1 Limiting K1 Neural networks K1 Supervised learning K1 Reliability K1 Noise measurement K1 Noisy label K1 Weakly supervised learning K1 Feature representation learning SP 1 OP 8 LK http://dx.doi.org/https://doi.org/10.1109/IJCNN55064.2022.9892045 DO https://doi.org/10.1109/IJCNN55064.2022.9892045 SF ELIB - SuUB Bremen
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