A depth neural network model clipping method based on statistical feature of feature graph
A deep neural network and statistical feature technology, applied in the field of pattern recognition and artificial intelligence, can solve problems such as being easily affected by bandwidth, low computing efficiency, and easy to destroy network parameter characteristics
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[0055] The present invention will be described in detail below in conjunction with specific examples, and the following examples will help those skilled in the art to further understand the present invention. The examples described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.
[0056] figure 1 It is a schematic flow chart of a deep neural network model clipping method based on feature map statistics in this example. By removing specific feature maps and corresponding convolution kernels, the network model framework can be reduced and the parameters can be compressed. The clipping method of the model, the specific implementation steps are:
[0057] (1) For the feature layer in the deep neural network, calculate the statistical features of each feature map in the feature layer in turn;
[0058] (2) Construct judging criteria based on statistical features;
[005...
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