Mobilenets: efficient convolutional neural networks for mobile vision applications

HIGHLIGHTS

• who: Andrew G. Howard and colleagues from the Google Inc have published the paper: MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications, in the Preprint: Arxiv of 17/04/2017
• what: The authors show results for MobileNet with depthwise separable convolutions compared to a model built with full convolutions. In a face attribute classification task, the authors demonstrate a synergistic relationship between MobileNet and distillation , a knowledge transfer technique for deep networks. The authors seek to reduce a large face attribute classifier with 75 million parameters and 1600 million Mult-Adds. The authors report . . .
  

   

  

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