Figure-Ground Organization in Natural Scenes: Performance of a Recurrent Neural Model Compared with Neurons of Area V2

Brian Hu; Rüdiger von der Heydt; Ernst Niebur

doi:10.1523/ENEURO.0479-18.2019

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Research ArticleNew Research, Sensory and Motor Systems

Figure-Ground Organization in Natural Scenes: Performance of a Recurrent Neural Model Compared with Neurons of Area V2

Brian Hu, Rüdiger von der Heydt and Ernst Niebur

eNeuro 5 June 2019, 6 (3) ENEURO.0479-18.2019; DOI: https://doi.org/10.1523/ENEURO.0479-18.2019

Brian Hu

1Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218

2Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205

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ORCID record for Brian Hu

Rüdiger von der Heydt

1Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218

3Solomon Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21205

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Ernst Niebur

1Zanvyl Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, MD 21218

3Solomon Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD 21205

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ORCID record for Ernst Niebur

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Figure-Ground Organization in Natural Scenes: Performance of a Recurrent Neural Model Compared with Neurons of Area V2

Brian Hu, Rüdiger von der Heydt, Ernst Niebur

eNeuro 5 June 2019, 6 (3) ENEURO.0479-18.2019; DOI: 10.1523/ENEURO.0479-18.2019

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Figure-Ground Organization in Natural Scenes: Performance of a Recurrent Neural Model Compared with Neurons of Area V2

Brian Hu, Rüdiger von der Heydt, Ernst Niebur

eNeuro 5 June 2019, 6 (3) ENEURO.0479-18.2019; DOI: 10.1523/ENEURO.0479-18.2019

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border ownership
natural scenes
neural networks
perceptual organization
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Figure-Ground Organization in Natural Scenes: Performance of a Recurrent Neural Model Compared with Neurons of Area V2

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