Exploiting temporal continuity of views to learn visual object invariance

Exploiting temporal continuity of views to learn visual object invariance

Bibliographic Details
Main Authors: Evgeniy eBart, Jay eHegdé
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-03-01
Series:Frontiers in Neuroscience
Subjects:
Perceptual Learning
trace learning
Invariant recognition
cortical model
invariance disruption
object constancy
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00026/full
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spelling doaj-065675e8447445889923a79bad919ef62020-11-24T23:47:49ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2013-03-01710.3389/fnins.2013.0002646540Exploiting temporal continuity of views to learn visual object invarianceEvgeniy eBart0Jay eHegdé1Palo Alto Research CenterGeorgia Regents Universityhttp://journal.frontiersin.org/Journal/10.3389/fnins.2013.00026/fullPerceptual Learningtrace learningInvariant recognitioncortical modelinvariance disruptionobject constancy
collection DOAJ
language English
format Article
sources DOAJ
author Evgeniy eBart
Jay eHegdé
spellingShingle Evgeniy eBart
Jay eHegdé
Exploiting temporal continuity of views to learn visual object invariance
Frontiers in Neuroscience
Perceptual Learning
trace learning
Invariant recognition
cortical model
invariance disruption
object constancy
author_facet Evgeniy eBart
Jay eHegdé
author_sort Evgeniy eBart
title Exploiting temporal continuity of views to learn visual object invariance
title_short Exploiting temporal continuity of views to learn visual object invariance
title_full Exploiting temporal continuity of views to learn visual object invariance
title_fullStr Exploiting temporal continuity of views to learn visual object invariance
title_full_unstemmed Exploiting temporal continuity of views to learn visual object invariance
title_sort exploiting temporal continuity of views to learn visual object invariance
publisher Frontiers Media S.A.
series Frontiers in Neuroscience
issn 1662-453X
publishDate 2013-03-01
topic Perceptual Learning
trace learning
Invariant recognition
cortical model
invariance disruption
object constancy
url http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00026/full
work_keys_str_mv AT evgeniyebart exploitingtemporalcontinuityofviewstolearnvisualobjectinvariance
AT jayehegde exploitingtemporalcontinuityofviewstolearnvisualobjectinvariance
_version_ 1725488450350612480

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