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When calculating the threshold, the weight ordering of all bn layers is used. Is this reasonable?
Is there such a phenomenon:
① The first value of the network is closer to the image pixel value, and the last layer is closer to the category probability. bn's weight is not necessarily the same.
② There is a shortcut in the middle of the network. After the two convolution pixel values are superimposed, the weight parameter becomes larger. May affect bn's weight.
When calculating the threshold, the weight ordering of all bn layers is used. Is this reasonable?
Is there such a phenomenon:
① The first value of the network is closer to the image pixel value, and the last layer is closer to the category probability. bn's weight is not necessarily the same.
② There is a shortcut in the middle of the network. After the two convolution pixel values are superimposed, the weight parameter becomes larger. May affect bn's weight.
在计算阈值时,将使用所有bn层的权重排序。 这合理吗?
是否存在这样的现象:
①网络最前面的数值,更靠近图像像素值,最后一层更靠近类别概率。bn的weight不一定分布相同。
②在网络中间有shortcut,两个卷积像素值叠加后,weight参数变大。可能会影响bn的weight。
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