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dc.contributor.authorWILSON, SIMON PAUL
dc.date.accessioned2009-09-18T17:04:03Z
dc.date.available2009-09-18T17:04:03Z
dc.date.issued2006
dc.date.submitted2006en
dc.identifier.citationS.P. Wilson and Georgios Stefanou `Improving CBIR by modelling the search process: a Bayesian approach? in Proceedings of the European Signal Processing Conference, Firenze, Italy, 2006, pp 1-4en
dc.identifier.otherN
dc.identifier.otherNen
dc.identifier.urihttp://hdl.handle.net/2262/32986
dc.descriptionPRESENTEDen
dc.description.abstractIn this paper we look at a simple image retrieval with relevance feedback scenario where we model simple properties of the search process. A content-based image retrieval method based on Bayesian inference is proposed that infers these search properties, as well as providing relevant images, from relevance feedback data. The approach is evaluated by performing searches for categories of image that invoke different emotional reactions.en
dc.description.sponsorshipThe images of paintings are courtesy of the Bridgeman Art Library, London (www.bridgeman.co.uk). This work has been made possible by the Network of Excellence MUSCLE, contract number FP6-507752 (www.muscle-noe.org), funded by the European Union.en
dc.format.extent1-4en
dc.format.extent201048 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.rightsYen
dc.subjectStatisticsen
dc.titleImproving CBIR by modelling the search process: a Bayesian approachen
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/swilson


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