I'm quite surprised so much was retained; many presentations on convolutional networks suggest adding a lot of features, but prune most in a post learning step.

I'm quite surprised so much was retained; many presentations on convolutional networks suggest adding a lot of features, but prune most in a post learning step. Supposedly lots of features, which are initialized randomly, just raise the probability of being close to the real answer (the concept being learned). Once it's found, most of features typically go unused or are reduntant.