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Convolutional neural network using a binarized convolution layer

  • US 9,563,825 B2
  • Filed: 11/20/2014
  • Issued: 02/07/2017
  • Est. Priority Date: 11/20/2014
  • Status: Active Grant
First Claim
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1. A method comprising:

  • obtaining, by at least one computing device, input data that is a set of training inputs for a convolutional neural network, the convolutional neural network including multiple layers, one of the multiple layers including a convolution layer, the convolution layer including one or more filters;

    training, by the at least one computing device, the convolutional neural network based on the set of training inputs;

    binarizing, by the at least one computing device, the convolution layer by converting parameters of the one or more filters from floating point to binary values;

    generating, by the at least one computing device, look-up table values of a look-up table for the binary values, the look-up table storing pre-computed results that are possible for the convolution layer; and

    outputting, by the at least one computing device, a result of the generating.

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