Learning from noisy labelsby importance reweighting: : a deep learning approach
Noisy labels could cause severe degradation to the classification performance. Especially for deep neural networks, noisy labels can be memorized and lead to poor generalization. Recently label noise robust deep learning has outperformed traditional shallow learning approaches in handling complex in...
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| Format: | Others |
| Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2019
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264125 |