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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.

I promised some links, so here they come!

The paper "A Neural Algorithm of Artistic Style" is available here:
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:

Picasso meets Gandalf:

A nice website with many results:

More examples with Picasso and some sketches:

Google DeepMind's Deep Q-learning algorithm plays Atari games:

The first implementations / source code packages are now available:

A great read on Deep Dreaming Neural Networks:

Many of you have asked for the code. Some people were experimenting with it in the Machine Learning reddit. Check it out:

Subscribe if you would like to see more of these! -

Splash screen/thumbnail design: Felícia Fehér -

Epilog - Ghostpocalypse by Kevin MacLeod is licensed under a Creative Commons Attribution license (


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