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Learning Deep Features for Discriminative Localization

Learning Deep Features for Discriminative Localization

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weights of the output layer on to the convolutional feature maps, a technique we call class activation mapping. As illustrated in Fig. 2, global average pooling outputs the spatial average of the feature map of each unit at the last convolutional layer. A weighted sum of these values is used to generate the final output. Similarly, we compute a

  Feature, Deep, Activation, Convolutional, Convolutional features

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