Literature DB >> 30728275

Do Primates and Deep Artificial Neural Networks Perform Object Categorization in a Similar Manner?

Prabaha Gangopadhyay1, Jhilik Das2.   

Abstract

Mesh：

Year:  2019        PMID： 30728275      PMCID： PMC6363923          DOI： 10.1523/JNEUROSCI.2458-18.2018

Source DB:  PubMed          Journal:  J Neurosci        ISSN： 0270-6474            Impact factor:   6.167


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  15 in total

1.  Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream.

Authors:  Umut Güçlü; Marcel A J van Gerven
Journal:  J Neurosci       Date:  2015-07-08       Impact factor: 6.167

2.  Nonlinear Y-Like Receptive Fields in the Early Visual Cortex: An Intermediate Stage for Building Cue-Invariant Receptive Fields from Subcortical Y Cells.

Authors:  Amol Gharat; Curtis L Baker
Journal:  J Neurosci       Date:  2017-01-25       Impact factor: 6.167

3.  Performance-optimized hierarchical models predict neural responses in higher visual cortex.

Authors:  Daniel L K Yamins; Ha Hong; Charles F Cadieu; Ethan A Solomon; Darren Seibert; James J DiCarlo
Journal:  Proc Natl Acad Sci U S A       Date:  2014-05-08       Impact factor: 11.205

4.  Interaction between Scene and Object Processing Revealed by Human fMRI and MEG Decoding.

Authors:  Talia Brandman; Marius V Peelen
Journal:  J Neurosci       Date:  2017-07-07       Impact factor: 6.167

5.  Scene consistency in object and background perception.

Authors:  Jodi L Davenport; Mary C Potter
Journal:  Psychol Sci       Date:  2004-08

6.  Dynamics of 3D view invariance in monkey inferotemporal cortex.

Authors:  N Apurva Ratan Murty; Sripati P Arun
Journal:  J Neurophysiol       Date:  2015-01-21       Impact factor: 2.714

7.  Deep supervised, but not unsupervised, models may explain IT cortical representation.

Authors:  Seyed-Mahdi Khaligh-Razavi; Nikolaus Kriegeskorte
Journal:  PLoS Comput Biol       Date:  2014-11-06       Impact factor: 4.475

Review 8.  The functional neuroanatomy of face perception: from brain measurements to deep neural networks.

Authors:  Kalanit Grill-Spector; Kevin S Weiner; Jesse Gomez; Anthony Stigliani; Vaidehi S Natu
Journal:  Interface Focus       Date:  2018-06-15       Impact factor: 3.906

9.  The spatial structure of a nonlinear receptive field.

Authors:  Gregory W Schwartz; Haruhisa Okawa; Felice A Dunn; Josh L Morgan; Daniel Kerschensteiner; Rachel O Wong; Fred Rieke
Journal:  Nat Neurosci       Date:  2012-09-23       Impact factor: 24.884

10.  The influence of scene context on object recognition is independent of attentional focus.

Authors:  Jaap Munneke; Valentina Brentari; Marius V Peelen
Journal:  Front Psychol       Date:  2013-08-20
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  1 in total

1.  Context-Aware Superpixel and Bilateral Entropy-Image Coherence Induces Less Entropy.

Authors:  Feihong Liu; Xiao Zhang; Hongyu Wang; Jun Feng
Journal:  Entropy (Basel)       Date:  2019-12-23       Impact factor: 2.524
  1 in total

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