Modular Common Vector Approach

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dc.authoridKoc, Mehmet/0000-0003-2919-6011
dc.contributor.authorKoc, Mehmet
dc.contributor.authorBarkana, Atalay
dc.date.accessioned2025-05-20T19:01:04Z
dc.date.issued2014
dc.departmentBilecik Şeyh Edebali Üniversitesi
dc.description22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEY
dc.description.abstractThe performance of a face recognition system is negatively affected by the accessories used on the face Like many methods, the recognition performance of the Common Vector Approach (CVA) [1] over occluded images is not at the desired level. In this work, we proposed an extension of the CVA, namely the Modular Common Vector Approach (M-CVA), which improves the recognition performance at the occluded face images. M-CVA outperforms CVA by a margin of 82,7 percent in the experiments which are conducted over AR face database.
dc.description.sponsorshipIEEE,Karadeniz Tech Univ, Dept Comp Engn & Elect & Elect Engn
dc.identifier.endpage535
dc.identifier.isbn978-1-4799-4874-1
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-84903767217
dc.identifier.scopusqualityN/A
dc.identifier.startpage533
dc.identifier.urihttps://hdl.handle.net/11552/8971
dc.identifier.wosWOS:000356351400112
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWoS
dc.indekslendigikaynakScopus
dc.indekslendigikaynakWoS - Conference Proceedings Citation Index-Science
dc.language.isotr
dc.publisherIeee
dc.relation.ispartof2014 22nd Signal Processing and Communications Applications Conference (Siu)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250518
dc.subjectcommon vector approach
dc.subjectface recognition
dc.subjectocclusion
dc.titleModular Common Vector Approach
dc.typeConference Object

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