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In a Convolutional Layer of a given Convolutional Neural Network there is a defined input of size NxMxD. Whereas N and M stand for a dimension of an input image (can be smaller than the original size of an image due to pooling) and as I understand, D stands for a number of filters used in Convolution. My question is how network decides, what are the best filters for a given layer?
submitted by /u/rathernot000
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