Deep neural network feature visualization method for constrained optimization class activation mapping
A deep neural network and constrained optimization technology, which is applied in the field of constrained optimization class activation mapping deep neural network feature visualization, can solve the problems of weak class discrimination and large noise, and achieve strong class discrimination, less noise, and good visual effects Effect
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[0041] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.
[0042] According to the example that the complete method of content of the present invention implements and its implementation situation are as follows:
[0043] The embodiment uses the deep neural network VGG19 trained on the ImageNet data set as the target model, and is described in detail as follows:
[0044] 1) Obtain a pre-trained model by training or downloading. Torchvision provides a pre-trained VGG19 model on the ImageNet dataset, which can be directly loaded and used.
[0045] 2) Set the feature map to be used, that is, the output of a certain layer of the VGG19 model as the feature map used for subsequent visualization, for example, select the output "features.34" of the last convolutional layer of VGG19.
[0046] 3) For an image X to be tested, such as figure 2 As shown, the input pre-training model is forwarded to obt...
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