Sparse Convolutional Neural Networks

  title={Sparse Convolutional Neural Networks},
  author={Baoyuan Liu and Min Wang and Hassan Foroosh and Marshall F. Tappen and Marianna Pensky},
  journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
Deep neural networks have achieved remarkable performance in both image classification and object detection problems, at the cost of a large number of parameters and computational complexity. In this work, we show how to reduce the redundancy in these parameters using a sparse decomposition. Maximum sparsity is obtained by exploiting both inter-channel and intra-channel redundancy, with a fine-tuning step that minimize the recognition loss caused by maximizing sparsity. This procedure zeros out… CONTINUE READING
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