2021
DOI: 10.7287/peerj-cs.454v0.1/reviews/1
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Peer Review #1 of "AresB-Net: accurate residual binarized neural networks using shortcut concatenation and shuffled grouped convolution (v0.1)"

Abstract: This paper 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 (BNNs) with increasing feature resolution, the degraded classification accuracy is still the primary concern compared with real-valued residual CNNs. AresB-Net consists of novel basic blocks to amortize the severe error from the binarization, suggesting a well-balanced pyrami… Show more

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