XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
這篇文章提出了兩個二進制類的網絡模型，一個叫做Binary-Weighted-Networks，一個叫做XNOR-Net。其中BWN只有filter是二進制的表達，而XNOR-Net在input和filter上都是二進制的表達。其中指出二進制的表達XNOR-Nets在執行卷積運算時能夠提升58×的速度，而可以節省32×的內存空間，這爲XNOR-Nets在CPU上運行提供了可能性。 Binary-W
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相關文章
- 1. ImageNet Classification with Deep Convolutional Neural Networks
- 2. XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
- 3. AlexNet解析：ImageNet Classification with Deep Convolutional Neural Networks
- 4. XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks 論文筆記
- 5. 二值網絡--XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks
- 6. Local Binary Convolutional Neural Networks
- 7. ImageNet Classification with Deep Convolutional Neural Networks
- 8. Diffusion-Convolutional Neural Networks
- 9. 讀文獻——《ImageNet classification with deep convolutional neural networks》
- 10. Chained Predictions Using Convolutional Neural Networks