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Please use this identifier to cite or link to this item: https://olympias.lib.uoi.gr/jspui/handle/123456789/10962
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dc.contributor.authorTzikas, D.en
dc.contributor.authorLikas, A.en
dc.contributor.authorGalatsanos, N.en
dc.date.accessioned2015-11-24T17:01:40Z-
dc.date.available2015-11-24T17:01:40Z-
dc.identifier.issn0218-2130-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/10962-
dc.rightsDefault Licence-
dc.subjectrelevance vector machineen
dc.subjectobject detectionen
dc.subjectimage analysisen
dc.titleLarge scale multikernel relevance vector machine for object detectionen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικήςel
heal.publicationDate2007-
heal.abstractThe Relevance Vector Machine(RVM) is a widely accepted Bayesian model commonly used for regression and classification tasks. In this paper we propose a multikernel version of the RVM and present an alternative inference algorithm based on Fourier domain computation to solve this model for large scale problems, e.g. images. We then apply the proposed method to the object detection problem with promising results.en
heal.journalNameInternational Journal on Artificial Intelligence Toolsen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
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