PLANT IDENTIFICATION USING LOCAL INVARIANTS

dc.authoridYanikoglu, Berrin/0000-0001-7403-7592
dc.authorwosidYanikoglu, Berrin/AAE-4843-2022
dc.authorwosidAptoula, Erchan/AAI-1070-2020
dc.contributor.authorYildiran, S. Tolga
dc.contributor.authorYanikoglu, Berrin
dc.contributor.authorAbdullah, Erhan
dc.date.accessioned2024-10-15T20:18:49Z
dc.date.available2024-10-15T20:18:49Z
dc.date.issued2014
dc.departmentOkan Universityen_US
dc.department-temp[Yildiran, S. Tolga; Yanikoglu, Berrin] Sabanci Univ, Muhendislik & Doga Bilimleri Fak, Istanbul, Turkey; [Abdullah, Erhan] Okan Univ, Bilgisayar Muhendisligi Bolumu, Istanbul, Turkeyen_US
dc.descriptionYanikoglu, Berrin/0000-0001-7403-7592en_US
dc.description.abstractWe present a plant image recognition system geared towards plants with flowers. The system uses local invariants with Dense SIFT features and Bag of Visual Words representation, while the classification is done using Support Vector Machines. Our approach contains a pre-classification stage where images are categorized into color subgroups, to reduce the complexity of the problem. Using a 161-class subset of the ImageClef'2013 flower dataset, the classification accuracy is measured as %42.68, compared to %18 eithout the pre-classification.en_US
dc.description.woscitationindexConference Proceedings Citation Index - Science
dc.identifier.citation0
dc.identifier.doi[WOS-DOI-BELIRLENECEK-175]
dc.identifier.endpage2097en_US
dc.identifier.isbn9781479948741
dc.identifier.issn2165-0608
dc.identifier.startpage2094en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14517/6413
dc.identifier.wosWOS:000356351400503
dc.language.isotr
dc.publisherIeeeen_US
dc.relation.ispartof22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEYen_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDense SIFT K Means Clusteringen_US
dc.subjectBag of Visual Words (BOVW)en_US
dc.subjectSVMsen_US
dc.subjectPHOWen_US
dc.titlePLANT IDENTIFICATION USING LOCAL INVARIANTSen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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