Feature dispersion degree-based attention mechanism method and system
A technology of discreteness and attention, applied in the field of image processing, can solve the problems of losing the importance of features, weakening the importance of features, affecting the redistribution of feature map weights, etc., to achieve the effect of optimizing channel weight distribution and improving performance
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[0041] The present application will be further described in detail below with reference to the accompanying drawings.
[0042] In the embodiments of the present application, in order to optimize the weight distribution of the neural network to the feature map and improve the performance of the neural network in classification and detection, an attention mechanism method and system based on the discrete degree of features are specifically disclosed. refer to figure 1 , is a flow chart of the steps of the attention mechanism method based on the degree of feature discreteness, including:
[0043] S10: Based on the initial feature map, obtain the target variance corresponding to the pixel value in the initial feature map;
[0044] S20: Based on the target variance and the sigmoid activation function, obtain the target weight value;
[0045] S30: Obtain a target feature map based on the target weight value and the initial feature map;
[0046] Among them, in the channel attentio...
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