Imagine I have a tensorflow CNN model with good accuracy but maybe too many filters:
Is there a way to determine which filters have more impact in output? I think it should be possible. At least, if a filter A has a 0, that only multiples the output of a filter B, then filter B is not related to filter A. In particular, I'm thinking in 2d data where 1 dimension is time-related and the other feature related (like one-hot char).
Is there a way to eliminate the less relevant filters from a trained model, and leave the rest of the model intact?
Is it useful or there are better methods?