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  Texture and art with deep neural networks

Gatys, L., Ecker, A., & Bethge, M. (2017). Texture and art with deep neural networks. Current Opinion in Neurobiology, 46, 178-186. doi:10.1016/j.conb.2017.08.019.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-C2A8-7 Version Permalink: http://hdl.handle.net/21.11116/0000-0000-F96D-E
Genre: Journal Article

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Gatys, LA, Author
Ecker, AS, Author              
Bethge, M1, 2, Author              
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              

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 Abstract: Although the study of biological vision and computer vision attempt to understand powerful visual information processing from different angles, they have a long history of informing each other. Recent advances in texture synthesis that were motivated by visual neuroscience have led to a substantial advance in image synthesis and manipulation in computer vision using convolutional neural networks (CNNs). Here, we review these recent advances and discuss how they can in turn inspire new research in visual perception and computational neuroscience.

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 Dates: 2017-10
 Publication Status: Published in print
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 Identifiers: DOI: 10.1016/j.conb.2017.08.019
BibTex Citekey: GatysEB2017
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Title: Current Opinion in Neurobiology
Source Genre: Journal
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Pages: - Volume / Issue: 46 Sequence Number: - Start / End Page: 178 - 186 Identifier: -