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Inaccurate labels in weakly-supervised deep learning: Automatic identification and correction and their impact on classification performance
In data-driven deep learning-based modeling, data quality may substantially influence classification performance. Correct data labeling for deep learning modeling is critical. In weakly-supervised learning, a challenge lies in dealing with potentially inaccurate or mislabeled training data. In this...
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| Publicado no: | IEEE J Biomed Health Inform |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7429345/ https://ncbi.nlm.nih.gov/pubmed/32078570 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/JBHI.2020.2974425 |
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