Robust feature space separation for deep convolutional neural network training
Abstract This paper introduces two deep convolutional neural network training techniques that lead to more robust feature subspace separation in comparison to traditional training. Assume that dataset has M labels. The first method creates M deep convolutional neural networks called $$\{\text {DCNN}...
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| Auteurs principaux: | , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Springer
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/0c4975ea7511433cbff1e6d106499b8e |
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