When an image is fed into a CNN, it would pass through different layer of different filters. The visualization of these filters look like:
Here we can safely claim that the 1st filter is more activated than the 2nd hence it carry more weight in identifying the input image. My questions is, how do we quantitatively compute the "activation" (or the usefulness) of a filter?
I have tried 3 approaches: by brightness, by variance and by Shannon entropy. Yet none of them working perfectly so far.
When measure them by brightness, I got upper image brighter than the lower image:
When measure them by Shannon entropy, I got upper image with higher entropy than the lower image:
So, any suggestion how could I measure their's activation?
