Literature DB >> 28926765

Texture and art with deep neural networks.

Leon A Gatys1, Alexander S Ecker2, Matthias Bethge3.   

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.
Copyright © 2017. Published by Elsevier Ltd.

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Year:  2017        PMID: 28926765     DOI: 10.1016/j.conb.2017.08.019

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  4 in total

1.  Examining the Coding Strength of Object Identity and Nonidentity Features in Human Occipito-Temporal Cortex and Convolutional Neural Networks.

Authors:  Yaoda Xu; Maryam Vaziri-Pashkam
Journal:  J Neurosci       Date:  2021-03-31       Impact factor: 6.167

Review 2.  Application of machine learning in predicting hospital readmissions: a scoping review of the literature.

Authors:  Yinan Huang; Ashna Talwar; Satabdi Chatterjee; Rajender R Aparasu
Journal:  BMC Med Res Methodol       Date:  2021-05-06       Impact factor: 4.615

3.  Deep Synthesis of Realistic Medical Images: A Novel Tool in Clinical Research and Training.

Authors:  Evgeniy Bart; Jay Hegdé
Journal:  Front Neuroinform       Date:  2018-11-20       Impact factor: 4.081

4.  Limits to visual representational correspondence between convolutional neural networks and the human brain.

Authors:  Yaoda Xu; Maryam Vaziri-Pashkam
Journal:  Nat Commun       Date:  2021-04-06       Impact factor: 14.919

  4 in total

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