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dc.contributor.authorOzer, Sedat
dc.contributor.authorKabaoglu, Nihat
dc.contributor.authorCirpan, Hakan A.
dc.date.accessioned2021-03-02T22:58:33Z
dc.date.available2021-03-02T22:58:33Z
dc.identifier.citationOzer S., Cirpan H. A. , Kabaoglu N., "Support vector regression for surveillance purposes", MULTIMEDIA CONTENT REPRESENTATION, CLASSIFICATION AND SECURITY, cilt.4105, ss.442-449, 2006
dc.identifier.issn0302-9743
dc.identifier.othervv_1032021
dc.identifier.otherav_0fb9b72a-d933-4297-9714-e51b0607527b
dc.identifier.urihttp://hdl.handle.net/20.500.12627/16108
dc.description.abstractThis paper addresses the problem of applying powerful statistical pattern classification algorithm based on kernel functions to target tracking on surveillance systems. Rather than directly adapting a recognizer, we develop a localizer directly using the regression form of the Support Vector Machines (SVM). The proposed approach considers to use dynamic model together as feature vectors and makes the byperplane and the support vectors follow the changes in these features. The performance of the tracker is demonstrated in a sensor network scenario with a constant velocity moving target on a plane for surveillance purpose.
dc.language.isoeng
dc.subjectBiyoenformatik
dc.subjectMühendislik ve Teknoloji
dc.subjectBilgisayar Bilimleri
dc.subjectBilgi Güvenliği ve Güvenilirliği
dc.subjectBİLGİSAYAR BİLİMİ, TEORİ VE YÖNTEM
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectBilgisayar Bilimi
dc.subjectBİLGİSAYAR BİLİMİ, BİLGİ SİSTEMLERİ
dc.titleSupport vector regression for surveillance purposes
dc.typeMakale
dc.relation.journalMULTIMEDIA CONTENT REPRESENTATION, CLASSIFICATION AND SECURITY
dc.contributor.department, ,
dc.identifier.volume4105
dc.identifier.startpage442
dc.identifier.endpage449
dc.contributor.firstauthorID177338


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