Deep Neural Network Learns Van Gogh's Art | Two Minute Papers #6
Artificial neural networks were inspired by the human brain and simulate how neurons behave when they are shown a sensory input (e.g., images, sounds, etc). They are known to be excellent tools for image recognition, any many other problems beyond that - they also excel at weather predictions, breast cancer cell mitosis detection, brain image segmentation and toxicity prediction among many others. Deep learning means that we use an artificial neural network with multiple layers, making it even more powerful for more difficult tasks. 

This time they have been shown to be apt at reproducing the artistic style of many famous painters, such as Vincent Van Gogh and Pablo Picasso among many others. All the user needs to do is provide an input photograph and a target image from which the artistic style will be learned.
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I promised some links, so here they come!

The paper "A Neural Algorithm of Artistic Style" is available here:
http://arxiv.org/abs/1508.06576v1
Disclaimer: I was not part of this research project, I am merely providing commentary on this work.

Recommended for you - Two Minute Papers episode on Artificial Neural Networks:
https://www.youtube.com/watch?v=rCWTOOgVXyE&index=3&list=PLujxSBD-JXgnqDD1n-V30pKtp6Q886x7e

Picasso meets Gandalf:
http://mashable.com/2015/08/29/computer-photos/

A nice website with many results:
https://deepart.io/

More examples with Picasso and some sketches:
http://imgur.com/a/jeJB6

Google DeepMind's Deep Q-learning algorithm plays Atari games:
https://www.youtube.com/watch?v=V1eYniJ0Rnk

The first implementations / source code packages are now available:
1. http://gitxiv.com/posts/jG46ukGod8R7Rdtud/a-neural-algorithm-of-artistic-style
2. https://github.com/kaishengtai/neuralart
3. https://github.com/jcjohnson/neural-style

A great read on Deep Dreaming Neural Networks:
http://googleresearch.blogspot.co.uk/2015/06/inceptionism-going-deeper-into-neural.html

Many of you have asked for the code. Some people were experimenting with it in the Machine Learning reddit. Check it out:
https://www.reddit.com/r/MachineLearning/comments/3imx1m/a_neural_algorithm_of_artistic_style/

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Music:
Epilog - Ghostpocalypse by Kevin MacLeod is licensed under a Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/)
Source: http://incompetech.com/music/royalty-free/index.html?isrc=USUAN1100666
Artist: http://incompetech.com/

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 Dear Fellow Scholars, this is two-minute papers with Karo Zsolnai-Fair and this paper is as fresh as it gets. As of the making of this video, it has been out for only one day and I got so excited about it that I wanted to show it to you Fellow Scholars as soon as humanly possible because you've got to see this. Not so long ago we have been talking about deep neural networks, a technique that was inspired by the human visual system. It enables computers to learn things in a very similar way that a human would. There is a previous two-minute papers episode on this, just click on the link in the description box if you've missed it. Neural networks are by no means perfect, so do not worry, don't quit your job, you're good. But some applications are getting out of control. In Google DeepMind's case, it started to learn playing simple computer games and eventually showed us superhuman level plays in some cases. So, if you've run this piece of code and got some pretty sweet results that you can check out, there's a link to it in the description box as well. So, about this paper we have here today, what does this one do? You take photographs with your camera and you can assign it any painting and it will apply this painting's artistic style to it. You can add the artistic style of Vincent van Gogh's beautiful story and get some gorgeous results. Or, if you are looking for a bit more emotional or may I say disturbed look, you can go for Edward Monks' The Scream for some stunning results. And of course, the mandatory Picasso. So, as you can see, deep neural networks are capable of amazing things and we expect even more revolutionary works in the very near future. Thanks for watching and I'll see you next time.
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