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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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2021-03-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-454.pdf |