I think [0] or [1] might be a good place to start, depending on what you want to do with it. Both take a similar to this blog post, in that they also use the VG

I think [0] or [1] might be a good place to start, depending on what you want to do with it. Both take a similar to this blog post, in that they also use the VGG networks trained on ImageNet. Specifically, [0] uses Fisher Vector pooling on the highest layer of convolution features, and they report good performance on texture and scene datasets even though they used weights learned from ImageNet data. Plus, skipping the fully connected layers means you can in principle use any image size/resolution without worrying about the size of the model. [0]: http://arxiv.org/abs/1411.6836 http://arxiv.org/abs/1411.6836 [1]: https://arxiv.org/abs/1403.1840 https://arxiv.org/abs/1403.1840