Comparison Computerized Object Recognition Systems

dc.authoridsert, eser/0000-0002-8611-701X
dc.authoridtaskin, deniz/0000-0001-7374-8165
dc.authorscopusid58350904100
dc.authorscopusid56024082800
dc.authorscopusid54785347700
dc.authorscopusid59014880200
dc.authorscopusid56024482500
dc.authorwosidSERT, ESER/AAK-1852-2020
dc.authorwosidtaskin, deniz/KIC-9302-2024
dc.contributor.authorSert, E.
dc.contributor.authorPinar, Y.
dc.contributor.authorTaskin, D.
dc.contributor.authorTaskin, C.
dc.contributor.authorTopcubasi, N.
dc.contributor.otherBilişim Sistemleri ve Teknolojileri / Information Systems and Technology
dc.contributor.otherBilişim Sistemleri ve Teknolojileri / Information Systems and Technology
dc.date.accessioned2024-10-15T20:18:12Z
dc.date.available2024-10-15T20:18:12Z
dc.date.issued2013
dc.departmentOkan Universityen_US
dc.department-temp[Sert, E.] Trakya Univ, Dept Elect & Automat, Edirne, Turkey; [Pinar, Y.] Trakya Univ, Dept Machine, Edirne, Turkey; [Taskin, D.] Trakya Univ, Edirne, Turkey; [Taskin, C.] Trakya Univ, Dept Comp Technol & Programming, Edirne, Turkey; [Topcubasi, N.] Okan Univ, Dept Informat Syst & Technol, Istanbul, Turkeyen_US
dc.descriptionsert, eser/0000-0002-8611-701X; taskin, deniz/0000-0001-7374-8165en_US
dc.description.abstractNowadays, object recognition automation systems are used in many sectors. Structure of the object recognition system is important for producing correct and rapid results. In this study, object detection systems are designed to classify Starking and Granny Smith type apples and these are compared with each other. Both designed systems are based on the pattern recognition principles. Outputs of object recognition systems are compared with the actual results and it has been observed that suggested system produces high success rate object recognition results. According to this result, it has been determined that the success of MATLAB Simulink object recognition system is 95 percent and success of Harpia object recognition system is 80 percent. Therefore, the MATLAB-based object recognition system produces more stable and clear results.en_US
dc.description.woscitationindexScience Citation Index Expanded
dc.identifier.citationcount0
dc.identifier.endpage56en_US
dc.identifier.issn0084-5841
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-84893387961
dc.identifier.startpage50en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14517/6348
dc.identifier.volume44en_US
dc.identifier.wosWOS:000329146500019
dc.identifier.wosqualityQ4
dc.institutionauthorTopçubaşı, Nurşen
dc.institutionauthorTopçubaşı, Nurşen
dc.institutionauthorTopçubaşı, Nurşen
dc.language.isoen
dc.publisherFarm Machinery industrial Research Corpen_US
dc.relation.ispartofAMA, Agricultural Mechanization in Asia, Africa and Latin Americaen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.scopus.citedbyCount0
dc.subject[No Keyword Available]en_US
dc.titleComparison Computerized Object Recognition Systemsen_US
dc.typeArticleen_US
dc.wos.citedbyCount0
dspace.entity.typePublication
relation.isAuthorOfPublication45d7c7e4-0eb5-4f1c-b49c-21ecf933e4eb
relation.isAuthorOfPublication.latestForDiscovery45d7c7e4-0eb5-4f1c-b49c-21ecf933e4eb
relation.isOrgUnitOfPublicationa3e89023-d6e0-4c3e-b81b-3c4740bd74f7
relation.isOrgUnitOfPublication.latestForDiscoverya3e89023-d6e0-4c3e-b81b-3c4740bd74f7

Files