Quantized Convolutional Neural Networks for Mobile Devices

@article{Wu2016QuantizedCN,
  title={Quantized Convolutional Neural Networks for Mobile Devices},
  author={J. Wu and C. Leng and Yuhang Wang and Q. Hu and J. Cheng},
  journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={4820-4828}
}
  • J. Wu, C. Leng, +2 authors J. Cheng
  • Published 2016
  • Computer Science
  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Recently, convolutional neural networks (CNN) have demonstrated impressive performance in various computer vision tasks. However, high performance hardware is typically indispensable for the application of CNN models due to the high computation complexity, which prohibits their further extensions. In this paper, we propose an efficient framework, namely Quantized CNN, to simultaneously speed-up the computation and reduce the storage and memory overhead of CNN models. Both filter kernels in… Expand
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