Large scale multikernel relevance vector machine for object detection

dc.contributor.author	Tzikas, D.	en
dc.contributor.author	Likas, A.	en
dc.contributor.author	Galatsanos, N.	en
dc.date.accessioned	2015-11-24T17:01:40Z
dc.date.available	2015-11-24T17:01:40Z
dc.identifier.issn	0218-2130	-
dc.identifier.uri	https://olympias.lib.uoi.gr/jspui/handle/123456789/10962
dc.rights	Default Licence	-
dc.subject	relevance vector machine	en
dc.subject	object detection	en
dc.subject	image analysis	en
dc.title	Large scale multikernel relevance vector machine for object detection	en
heal.abstract	The 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.access	campus	-
heal.fullTextAvailability	TRUE	-
heal.journalName	International Journal on Artificial Intelligence Tools	en
heal.journalType	peer reviewed	-
heal.language	en	-
heal.publicationDate	2007	-
heal.recordProvider	Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικής	el
heal.type	journalArticle	-
heal.type.el	Άρθρο Περιοδικού	el
heal.type.en	Journal article	en

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