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dc.contributor.authorHans P. Op de Beeck*
dc.contributor.authorJudith C. Peters*
dc.contributor.authorRainer Goebel*
dc.date.accessioned2021-02-11T16:22:54Z
dc.date.available2021-02-11T16:22:54Z
dc.date.issued2016*
dc.date.submitted2016-01-19 14:05:46*
dc.identifier18260*
dc.identifier.issn16648714*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/50380
dc.description.abstractThe articles in this Research Topic provide a state-of-the-art overview of the current progress in integrating computational and empirical research on visual object recognition. Developments in this exciting multidisciplinary field have recently gained momentum: High performance computing enabled breakthroughs in computer vision and computational neuroscience. In parallel, innovative machine learning applications have recently become available for datamining the large-scale, high resolution brain data acquired with (ultra-high field) fMRI and dense multi-unit recordings. Finally, new techniques to integrate such rich simulated and empirical datasets for direct model testing could aid the development of a comprehensive brain model. We hope that this Research Topic contributes to these encouraging advances and inspires future research avenues in computational and empirical neuroscience.*
dc.languageEnglish*
dc.relation.ispartofseriesFrontiers Research Topics*
dc.subjectRC321-571*
dc.subjectQ1-390*
dc.subject.classificationthema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAN Neurosciencesen_US
dc.subject.otherobject recognition*
dc.subject.otherfMRI*
dc.subject.othermultimodal data integration*
dc.subject.otherneural networks*
dc.subject.otherinvariance*
dc.subject.othercomputational neuroscience*
dc.subject.otherComputer Vision*
dc.subject.otherFeature representation*
dc.subject.otherNeurophysiology*
dc.subject.otherventral visual pathway*
dc.titleIntegrating Computational and Neural Findings in Visual Object Perception*
dc.typebook
oapen.identifier.doi10.3389/978-2-88919-873-3*
oapen.relation.isPublishedBybf5ce210-e72e-4860-ba9b-c305640ff3ae*
oapen.relation.isbn9782889198733*
oapen.pages137*


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