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dc.contributor.authorTavus, Mustafa Resit
dc.contributor.authorEker, Muhammed Emin
dc.contributor.authorSenyer, Nurettin
dc.contributor.authorKarabulut, Bunyamin
dc.date.accessioned2020-06-21T13:51:04Z
dc.date.available2020-06-21T13:51:04Z
dc.date.issued2015
dc.identifier.isbn978-1-4673-7386-9
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/20.500.12712/14570
dc.description23nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEYen_US
dc.descriptionWOS: 000380500900245en_US
dc.description.abstractIn this study, Plant Counting was implemented by appling k-NN classification to images obtained from Unnamed Air Vehicle (UAV). Firstly, The images were subjected to erosion process by transforming different colour levels. The objects in the images were classified as plant and soil by means of k-NN classification. It was observed that plants can be counted with 87,7% of accuracy and 86,6% of precision by being performed last processing of the morphology of the binary image.en_US
dc.description.sponsorshipDept Comp Engn & Elect & Elect Engn, Elect & Elect Engn, Bilkent Univen_US
dc.language.isoturen_US
dc.publisherIeeeen_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectk-NN algorithmen_US
dc.subjectplant countingen_US
dc.subjectimage processingen_US
dc.titlePlant Counting By Using k-NN Classification on UAVs Imagesen_US
dc.typeconferenceObjecten_US
dc.contributor.departmentOMÜen_US
dc.identifier.startpage1058en_US
dc.identifier.endpage1061en_US
dc.relation.journal2015 23Rd Signal Processing and Communications Applications Conference (Siu)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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