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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZG2LgkFdY/RD2vi
Repositorysid.inpe.br/sibgrapi@80/2007/10.02.15.36
Last Update2007:10.02.15.45.49 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi@80/2007/10.02.15.36.16
Metadata Last Update2022:05.18.22.21.16 (UTC) administrator
Citation KeyDonattiWürt:2007:MeOrIn
TitleMemory Organization for Invariant Object Recognition and Categorization
FormatOn-line
Year2007
Access Date2024, May 02
Number of Files1
Size59 KiB
2. Context
Author1 Donatti, Guillermo S.
2 Würtz, Rolf P.
Affiliation1 Institut für Neuroinformatik, International Graduate School of Neuroscience, Ruhr-Universität Bochum
2 Institut für Neuroinformatik, International Graduate School of Neuroscience, Ruhr-Universität Bochum
EditorGonçalves, Luiz
Wu, Shin Ting
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)
Conference LocationBelo Horizonte, MG, Brazil
Date7-10 Oct. 2007
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeTechnical Poster
History (UTC)2008-07-17 14:03:08 :: sdonatti@neuroinformatik.rub.de -> administrator ::
2008-07-17 14:05:11 :: administrator -> banon ::
2008-07-17 14:07:07 :: banon -> administrator ::
2009-08-13 20:38:49 :: administrator -> banon ::
2010-08-28 20:02:33 :: banon -> administrator ::
2022-05-18 22:21:16 :: administrator -> :: 2007
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsComputer Vision
Theoretical Neuroscience
Neuroscience
AbstractThe integration of bottom-up with top-down object processing has always been a topic of major concern in computer vision. However, while a lot is known about feature extraction, the knowledge-driven aspect of perception has been recognized as important, but hard to probe experimentally and difficult to implement in computer vision systems. How object knowledge must be organized so that it supports scene perception and can be acquired automatically is a research problem of outstanding significance for the biological, the psychological, and the computational approach to understand perception. The present work aims to develop an object memory model which can provide fast retrieval and robust recognition and categorization. The underlying data structure is inspired by the neural network structure of the human brain, connecting similar object views with excitatory synapses and using inhibitory synapses to separate different ones. The insights derived from building such a computational theory and the properties of the resulting model have implications for strategies and experimental paradigms to analyze human object memory as well as technical applications for robotics and computer vision.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2007 > Memory Organization for...
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source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/RD2vi
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/RD2vi
Languageen
Target Filesibgrapi_donatti_final.pdf
User Groupsdonatti@neuroinformatik.rub.de
administrator
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/sibgrapi@80/2007/08.02.16.22
Next Higher Units8JMKD3MGPEW34M/46SF8Q5
Citing Item Listsid.inpe.br/sibgrapi/2022/05.14.00.14 3
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi e-mailaddress edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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