<p>Have a look at <a href="https://arxiv.org/abs/1707.06168" rel="nofollow noreferrer">Channel Pruning</a>, <em>ICCV 2017</em>, an elegant algorithm that effectively prune channels each layer. In its <a href="https://github.com/yihui-he/channel-pruning" rel="nofollow noreferrer">github code</a>, there's a pruning process for removing unnecessary neurons, which helps reducing model size and accelerating prediction.</p>
Caffe- How to remove unwanted connections from an trained caffe model?
<p>I have trained a fastercnn model to detect human faces in an image using caffe. My current model size is 530MB. I wanted to reduce the size of my model, so I came accross <a href="https://arxiv.org/abs/1510.00149" rel="nofollow noreferrer">Deep Compression</a> By Song Han. </p>

<p>I've updated the less significant weights with 0 in my model using Pycaffe. The model size isn't reduced now, how to remove those insignificant connections from the trained caffe model, so that the size of the model is reduced?</p>