How do I obtain filters from convolutional neural network(CNN)? My idea is something like this: do random images of the input images (28x28) and get random patches (8x8). Then use autoencoders to learn the common features of the patches (features = hidden units; approximately 100, for example). Then apply features filters to the input images and do convolution. Am I correct?
I am confused because sometime the literature state only using like, e.g. 8, filters, but in my case I have 100.