In CNN (Convolutional Neural Network), does the combination of previous layer's filters make next layer's filters?
I guess you are making mistake about the filters. After applying filters to the input of each layer, the output will be used as the input of the next layer. The first layer's filters try to find the edges in the image and their output show whether those edges exist in a specified position or not. Next layer filters try to find patterns in the outputs of the previous layer which shows the existence of edges. Due to the point that each filter is a window and specifies a receptive field on the input, it finds patterns in the input which are more abstract and more complicated than the previous layers' activations.