Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/18925
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dc.contributor.authorLozo, Peteren
dc.date.issued1996en
dc.identifier.urihttp://hdl.handle.net/2440/18925-
dc.descriptionBibliography: leaves 328-352.en
dc.descriptionxxxi, 352 leaves : ill. ; 30 cm.en
dc.description.abstractThis thesis proposes a neural theory, Selective Attention Adaptive Resonance Theory, and a neuro-engineered solution to selective visual attention, memory guided processing and illumination invariant recognition of complete (unoccluded), but distorted 2D shapes of 3D objects in cluttered visual images.en
dc.format.extent209681 bytesen
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.subject.lcshVisual perception.en
dc.subject.lcshNeural networks (Computer science)en
dc.subject.lcshSimulation methods.en
dc.titleNeural theory and model of selective visual attention and 2D shape recognition in visual clutter / by Peter Lozo.en
dc.typeThesisen
dc.contributor.schoolDept. of Electrical and Electronic Engineeringen
dc.provenanceThis electronic version is made publicly available by the University of Adelaide in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. This thesis may incorporate third party material which has been used by the author pursuant to Fair Dealing exception. If you are the author of this thesis and do not wish it to be made publicly available or If you are the owner of any included third party copyright material you wish to be removed from this electronic version, please complete the take down form located at: http://www.adelaide.edu.au/legalsen
dc.description.dissertationThesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1997?en
Appears in Collections:Research Theses

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