Advanced Search

Show simple item record

dc.contributor.authorÖzer, Sedat
dc.contributor.authorÇırpan, Hakan Ali
dc.contributor.authorKabaoğlu, Nihat
dc.date.accessioned2019-06-27T08:06:52Z
dc.date.available2019-06-27T08:06:52Z
dc.date.issued2006
dc.identifier.isbn978-1-4244-0238-0
dc.identifier.urihttps://hdl.handle.net/20.500.12469/1239
dc.description.abstractThis paper addresses the problem of aplying powerful statistical pattern classification algorithms based on kernels to target tracking. 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 using dynamic model together as feature vectors and makes the hyperplane and the support vectors follow the changes in these features. The performance of the tracker is demostrated in a sensor network scenario with a moving target in a polynomial route.en_US]
dc.language.isoturen_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectN/Aen_US
dc.titleSupport vector machines based target tracking techniquesen_US
dc.typeconferenceObjecten_US
dc.identifier.startpage369en_US
dc.identifier.endpage+
dc.relation.journal2006 IEEE 14th Signal Processing And Communications Applications, Vols 1 and 2en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.departmentYüksekokullar, Teknik Bilimler Meslek Yüksekokuluen_US
dc.identifier.wosWOS:000245347800094en_US
dc.institutionauthorÖzer, Sedaten_US
dc.institutionauthorÇırpan, Hakan Alien_US
dc.institutionauthorKabaoğlu, Nihaten_US
dc.relation.publicationcategoryN/Aen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record