A correspondence-based neural mechanism for position invariant feature processing

  • Poster presentation: Introduction We here focus on constructing a hierarchical neural system for position-invariant recognition, which is one of the most fundamental invariant recognition achieved in visual processing [1,2]. The invariant recognition have been hypothesized to be done by matching a sensory image of a particular object stimulated on the retina to the most suitable representation stored in memory of the higher visual cortical area. Here arises a general problem: In such a visual processing, the position of the object image on the retina must be initially uncertain. Furthermore, the retinal activities possessing sensory information are being far from the ones in the higher area with a loss of the sensory object information. Nevertheless, with such recognition ambiguity, the particular object can effortlessly and easily be recognized. Our aim in this work is an attempt to resolve such a general recognition problem. ...

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Author:Yasuomi D. Sato, Evgueni Jitsev, Philipp Wolfrum, Christoph von der Malsburg
Parent Title (English):BMC neuroscience 2009, 10(Suppl 1):P366
Document Type:Article
Year of Completion:2009
Year of first Publication:2009
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2009/09/20
Volume:10(Suppl 1)
© 2009 Sato et al; licensee BioMed Central Ltd.
Source:from Eighteenth Annual Computational Neuroscience Meeting: CNS*2009 Berlin, Germany. 18–23 July 2009
Institutes:Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS)
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Sammlungen:Sammlung Biologie / Sondersammelgebiets-Volltexte
Licence (German):License LogoDeutsches Urheberrecht