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RBCN: Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs
[article]
2019
arXiv
pre-print
Binarized convolutional neural networks (BCNNs) are widely used to improve memory and computation efficiency of deep convolutional neural networks (DCNNs) for mobile and AI chips based applications. However, current BCNNs are not able to fully explore their corresponding full-precision models, causing a significant performance gap between them. In this paper, we propose rectified binary convolutional networks (RBCNs), towards optimized BCNNs, by combining full-precision kernels and feature maps
arXiv:1908.07748v2
fatcat:g2qkaqoeibhu7pw6q46sbs7eje