Discrimination of Haploid and Diploid Maize Seeds Based on Deep Features

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dc.authoridDönmez, Emrah/0000-0003-3345-8344
dc.authorwosidDönmez, Emrah/W-2891-2017
dc.contributor.authorDonmez, Emrah
dc.date.accessioned2024-08-04T20:49:16Z
dc.date.available2024-08-04T20:49:16Z
dc.date.issued2020
dc.departmentİnönü Üniversitesien_US
dc.description28th Signal Processing and Communications Applications Conference (SIU) -- OCT 05-07, 2020 -- ELECTR NETWORKen_US
dc.description.abstractOne of the main processes in in vivo maternal haploid breeding method which is widely used in hybrid maize breeding in recent years is the separation of haploid and diploid individuals. Although different approaches have been proposed to make this distinction, the R1-nj color marker is widely and successfully used. The R1-nj color marker allows the visual separation of haploid and diploid individuals during the seed period. Nowadays, this distinction is done manually, causing loss of time and labor as well as high error. In this study, an open access dataset consisting of 3,000 maize seed images was used. The deep features from the FC6, FC7 and FC8 fully connected layers of the AlexNet architecture are classified with the support vector machine. 10-fold cross-validation test was used to evaluate model performances. Experimental results showed that the best classification performance is possible with 89.50% accuracy using deep features obtained from the FC6 fully connected layer.en_US
dc.description.sponsorshipIstanbul Medipol Univen_US
dc.identifier.doi10.1109/siu49456.2020.9302142
dc.identifier.isbn978-1-7281-7206-4
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-85100289893en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/siu49456.2020.9302142
dc.identifier.urihttps://hdl.handle.net/11616/99747
dc.identifier.wosWOS:000653136100116en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2020 28th Signal Processing and Communications Applications Conference (Siu)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjecthaploid maize seed identificationen_US
dc.subjectimage processingen_US
dc.subjectconvolutional neural networksen_US
dc.subjectdeep featuresen_US
dc.subjectartificial learningen_US
dc.titleDiscrimination of Haploid and Diploid Maize Seeds Based on Deep Featuresen_US
dc.typeConference Objecten_US

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