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AresB-Net: accurate residual binarized neural networks using shortcut concatenation and shuffled grouped convolution
This article proposes a novel network model to achieve better accurate residual binarized convolutional neural networks (CNNs), denoted as AresB-Net. Even though residual CNNs enhance the classification accuracy of binarized neural networks with increasing feature resolution, the degraded classifica...
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| Τόπος έκδοσης: | PeerJ Comput Sci |
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| Κύριος συγγραφέας: | |
| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
PeerJ Inc.
2021
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| Θέματα: | |
| Διαθέσιμο Online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8022573/ https://ncbi.nlm.nih.gov/pubmed/33834112 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj-cs.454 |
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