| 1. Identity statement | |
| Reference Type | Conference Paper (Conference Proceedings) |
| Site | sibgrapi.sid.inpe.br |
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
| Identifier | 6qtX3pFwXQZG2LgkFdY/RD2vi |
| Repository | sid.inpe.br/sibgrapi@80/2007/10.02.15.36 |
| Last Update | 2007:10.02.15.45.49 (UTC) administrator |
| Metadata Repository | sid.inpe.br/sibgrapi@80/2007/10.02.15.36.16 |
| Metadata Last Update | 2022:05.18.22.21.16 (UTC) administrator |
| Citation Key | DonattiWürt:2007:MeOrIn |
| Title | Memory Organization for Invariant Object Recognition and Categorization  |
| Format | On-line |
| Year | 2007 |
| Access Date | 2024, Sep. 19 |
| Number of Files | 1 |
| Size | 59 KiB |
| 2. Context | |
| Author | 1 Donatti, Guillermo S. 2 Würtz, Rolf P. |
| Affiliation | 1 Institut für Neuroinformatik, International Graduate School of Neuroscience, Ruhr-Universität Bochum 2 Institut für Neuroinformatik, International Graduate School of Neuroscience, Ruhr-Universität Bochum |
| Editor | Gonçalves, Luiz Wu, Shin Ting |
| Conference Name | Brazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI) |
| Conference Location | Belo Horizonte, MG, Brazil |
| Date | 7-10 Oct. 2007 |
| Publisher | Sociedade Brasileira de Computação |
| Publisher City | Porto Alegre |
| Book Title | Proceedings |
| Tertiary Type | Technical 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 Stage | completed |
| Transferable | 1 |
| Keywords | Computer Vision Theoretical Neuroscience Neuroscience |
| Abstract | The 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. |
| Arrangement | urlib.net > SDLA > Fonds > SIBGRAPI 2007 > Memory Organization for... |
| doc Directory Content | access |
| source Directory Content | there are no files |
| agreement Directory Content | there are no files |
| 4. Conditions of access and use | |
| data URL | http://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/RD2vi |
| zipped data URL | http://urlib.net/zip/6qtX3pFwXQZG2LgkFdY/RD2vi |
| Language | en |
| Target File | sibgrapi_donatti_final.pdf |
| User Group | sdonatti@neuroinformatik.rub.de administrator |
| Visibility | shown |
| 5. Allied materials | |
| Mirror Repository | sid.inpe.br/sibgrapi@80/2007/08.02.16.22 |
| Next Higher Units | 8JMKD3MGPEW34M/46SF8Q5 |
| Citing Item List | sid.inpe.br/sibgrapi/2022/05.14.00.14 18 |
| Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
| 6. Notes | |
| Empty Fields | archivingpolicy 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 |