dc.contributor.author | Koç, Mehmet | |
dc.contributor.author | Barkana, Atalay | |
dc.date.accessioned | 2019-10-21T20:41:13Z | |
dc.date.available | 2019-10-21T20:41:13Z | |
dc.date.issued | 2014 | |
dc.identifier.isbn | 9781479948741 | |
dc.identifier.uri | https://dx.doi.org/10.1109/SIU.2014.6830283 | |
dc.identifier.uri | https://hdl.handle.net/11421/20706 | |
dc.description | 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 -- 23 April 2014 through 25 April 2014 -- Trabzon -- 106053 | en_US |
dc.description.abstract | The 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 | en_US |
dc.language.iso | tur | en_US |
dc.publisher | IEEE Computer Society | en_US |
dc.relation.isversionof | 10.1109/SIU.2014.6830283 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Common Vector Approach | en_US |
dc.subject | Face Recognition | en_US |
dc.subject | Occlusion | en_US |
dc.title | Modular common vector approach [Modüler ortak vektör yaklaşimi] | en_US |
dc.type | conferenceObject | en_US |
dc.relation.journal | 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings | en_US |
dc.contributor.department | Anadolu Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü | en_US |
dc.identifier.startpage | 533 | en_US |
dc.identifier.endpage | 535 | en_US |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US] |
dc.contributor.institutionauthor | Barkana, Atalay | |