Koyuncu, MuratCetinkaya, BasarInformation Systems Engineering2024-10-062024-10-062015097814673738692165-0608[WOS-DOI-BELIRLENECEK-227]https://hdl.handle.net/20.500.14411/9020Koyuncu, Murat/0000-0003-1958-5945In 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.trinfo:eu-repo/semantics/closedAccessComponent based object detectionSVMfeature vectors, fusionConference ObjectN/AN/A565568WOS:000380500900120