XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
Abstract 本文是一篇經典的二值化weight和activations的文章，發表在ECCV2016.本文提出了兩種有效二值化的框架： XNOR−Net X N O R − N e t 以及 BWN B W N (Binary-Weight-Networks).在存儲方面可以節省32倍的memory。在 XNOR−Net X N O R − N e t 上weights以及卷積層的input
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相關文章
- 1. XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
- 2. XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks 論文筆記
- 3. 二值網絡--XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
- 4. ImageNet Classification with Deep Convolutional Neural Networks
- 5. 讀文獻——《ImageNet classification with deep convolutional neural networks》
- 6. alexnet筆記（ImageNet Classification with Deep Convolutional Neural Networks）
- 7. 論文ImageNet Classification with Deep Convolutional Neural Networks（Alexnet2012）
- 8. AlexNet——ImageNet Classification with Deep Convolutional Neural Networks
- 9. AlexNet《ImageNet Classification with Deep Convolutional Neural Networks》
- 10. ImageNet Classification with Deep Convolutional Neural Networks -- 解讀