The internet is full of pictures like this:
But how are the second/third/etc CNN layers able to extract features when the features are already extracted by the previous layers?
For example, the mid-level feature in the picture has a nose. When we apply this "nose" filter, the output feature map will be an image without the nose, right? Then, this feature map is passed to the next CNN layer, but how is it able to extract the "high-level feature" if the feature map given to it doesn't contain the nose? And the more layers we stack in CNN, the less meaningful data will be extracted in the latter layers.