Feature Fusion in Part-Based Object Detection
| dc.authorid | Koyuncu, Murat/0000-0003-1958-5945 | |
| dc.authorwosid | Koyuncu, Murat/C-9407-2017 | |
| dc.contributor.author | Koyuncu, Murat | |
| dc.contributor.author | Cetinkaya, Basar | |
| dc.contributor.other | Information Systems Engineering | |
| dc.date.accessioned | 2024-10-06T10:59:48Z | |
| dc.date.available | 2024-10-06T10:59:48Z | |
| dc.date.issued | 2015 | |
| dc.department | Atılım University | en_US |
| dc.department-temp | [Koyuncu, Murat] Atilim Univ, Bilisim Sistemleri Muhendisligi Bolumu, Ankara, Turkey; [Cetinkaya, Basar] Atilim Univ, Muhendisl Sistemlerinin Tasarimi & Modellenmesi, Ankara, Turkey | en_US |
| dc.description | Koyuncu, Murat/0000-0003-1958-5945 | en_US |
| dc.description.abstract | In this study, classification of complex objects in images as a whole is compared with classification of its distinctive components using different features. In addition, the impact of feature fusion in part-based object detection is investigated. Applied method, implemented system, conducted tests and their results are presented in this paper. Test results show that, even in the case of a good segmentation, object components are classified more successfully compared to whole object and feature fusion method improves the obtained results to a certain degree. | en_US |
| dc.description.woscitationindex | Conference Proceedings Citation Index - Science | |
| dc.identifier.citation | 0 | |
| dc.identifier.doi | [WOS-DOI-BELIRLENECEK-227] | |
| dc.identifier.endpage | 568 | en_US |
| dc.identifier.isbn | 9781467373869 | |
| dc.identifier.issn | 2165-0608 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.startpage | 565 | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.14411/9020 | |
| dc.identifier.wos | WOS:000380500900120 | |
| dc.identifier.wosquality | N/A | |
| dc.institutionauthor | Koyuncu, Murat | |
| dc.language.iso | tr | en_US |
| dc.publisher | Ieee | en_US |
| dc.relation.ispartof | 23nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEY | en_US |
| dc.relation.ispartofseries | Signal Processing and Communications Applications Conference | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Component based object detection | en_US |
| dc.subject | SVM | en_US |
| dc.subject | feature vectors, fusion | en_US |
| dc.title | Feature Fusion in Part-Based Object Detection | en_US |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
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