Making Deep Neural Networks Robust to Label Noise: Cross-Training With a Novel Loss Function

Making Deep Neural Networks Robust to Label Noise: Cross-Training With a Novel Loss Function

Deep neural networks (DNNs) have achieved astonishing results on a variety of supervised learning tasks owing to a large scale of well-labeled training data. However, as recent researches have pointed out, the generalization performance of DNNs is likely to sharply deteriorate when training data con...

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Bibliographic Details
Main Authors: Zhen Qin, Zhengwen Zhang, Yan Li, Jun Guo
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Deep neural networks
label noise
cross-training
loss function
data filtration
Online Access:https://ieeexplore.ieee.org/document/8834773/

Internet

https://ieeexplore.ieee.org/document/8834773/

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