title: Is it meaningful to remove layers with %100 sparsity in a CNN - VGG 16
body: <p>I am training an autoencoder by using VGG-16 as feature extraction. Whenever I check the sparsity (number of parameters equal to zero / total parameters) of the blocks, I noticed that Block 5 (deepest block of VGG-16) has %100 sparsity. As it is the most time consuming block for VGG architecture, I would like to remove it if possible. </p>
  
  <p>So, is it meaningful to remove CNN layers with %100 sparsity to increase performance as all of them are actually equal to zero? </p>