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dc.contributor.authorWijewickrema, Sudanthi N. R.
dc.contributor.authorPapliński, Andrew P.
dc.contributor.editorSkala, Václav
dc.date.accessioned2013-01-23T11:18:51Z-
dc.date.available2013-01-23T11:18:51Z-
dc.date.issued2005
dc.identifier.citationWSCG '2005: Posters: The 13-th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2005 in co-operation with EUROGRAPHICS, University of West Bohemia, Plzen, Czech Republic, p. 71-72.en
dc.identifier.isbn80-903100-8-7
dc.identifier.urihttp://wscg.zcu.cz/WSCG2005/Papers_2005/Poster/!WSCG2005_Poster_Proceedings_Final.pdf
dc.identifier.urihttp://hdl.handle.net/11025/919
dc.description.abstractIn this paper, we investigate the use of a neural network employing Genralised Hebbian Learning for the approximation of an image of a hypothetically ellipsoidal object as an ellipse. Further, we discuss how the same algorithm is used with higher dimensional data to model hyperellipsoids, with the basic aim at a specific application, namely the modelling of an object as an ellipsoid given a set of 3-dimensional points.en
dc.format2 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.relation.ispartofseriesWSCG '2005: Postersen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectanalýza hlavních komponentcs
dc.subjectlícování elipsycs
dc.subjectgeneralizované Hebbův zákon učenícs
dc.titleGeneralized Hebbian learning for ellipse fittingen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatedprincipal component analysisen
dc.subject.translatedellipse fittingen
dc.subject.translatedgeneralised Hebbian learningen
dc.type.statusPeer-revieweden
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