Interactive bivariate mode tree

dc.contributor.authorFlorek, Martin
dc.contributor.authorHauser, Helwig
dc.contributor.editorSkala, Václav
dc.date.accessioned2012-07-27T09:02:50Z
dc.date.available2012-07-27T09:02:50Z
dc.date.issued2011
dc.description.abstractKernel density estimation (KDE) is widely used statistical method to study distribution of the data. The problem with this method is choosing the right bandwidth. In our work we focus on semiautomatic bandwidth selection with the use of visual paradigm of the Mode Tree. We not only enhanced the bivariate mode tree visualization, which was only sketched by the authors, but we also developed a hybrid CPU/GPU implementation to improve the speed of the mode tree construction. Keywords: Mode Tree, Data Visualization, Kernel Density Estimation, GPU.en
dc.format6 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.citationWSCG ’2011: Poster Papers Proceedings: The 19th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision: University of West Bohemia, Plzen, Czech Republic, January 31 - February 3, 2011, p. 41-46.en
dc.identifier.isbn978-80-86943-81-7
dc.identifier.urihttp://wscg.zcu.cz/WSCG2011/!_2011_WSCG_Poster_Papers.pdf
dc.identifier.urihttp://hdl.handle.net/11025/414
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.relation.ispartofseriesWSCG ’2011: posters proceedingsen
dc.rights© Václav Skala - UNION Agencycs
dc.rights.accessopenAccessen
dc.subjectvizualizace datcs
dc.subjectjádrový odhad hustotycs
dc.subject.translatedmode treeen
dc.subject.translateddata visualizationen
dc.subject.translatedkernel density estimationen
dc.titleInteractive bivariate mode treeen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen

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