Automatic identification for field butterflies by convolutional neural networks

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dc.authoridKutucu, Hakan/0000-0001-7144-7246
dc.contributor.authorAlmryad, Ayad Saad
dc.contributor.authorKutucu, Hakan
dc.date.accessioned2024-09-29T15:57:34Z
dc.date.available2024-09-29T15:57:34Z
dc.date.issued2020
dc.departmentKarabük Üniversitesien_US
dc.description.abstractIn today's competitive conditions, producing fast, inexpensive and reliable solutions are an objective for engineers. Development of artificial intelligence and the introduction of this technology to almost all areas have created a need to minimize the human factor by using artificial intelligence in the field of image processing, as well as to make a profit in terms of time and labor. In this paper, we propose an automated butterfly species identification model using deep neural networks. We collected 44,659 images of 104 different butterfly species taken with different positions of butterflies, the shooting angle, butterfly distance, occlusion and background complexity in the field in Turkey. Since many species have a few image samples we constructed a field-based dataset of 17,769 butterflies with 10 species. Convolutional Neural Networks (CNNs) were used for the identification of butterfly species. Comparison and evaluation of the experimental results obtained using three different network structures are conducted. Experimental results on 10 common butterfly species showed that our method successfully identified various butterfly species. (C) 2020 Karabuk University. Publishing services by Elsevier B.V.en_US
dc.identifier.doi10.1016/j.jestch.2020.01.006
dc.identifier.endpage195en_US
dc.identifier.issn2215-0986
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85078859154en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage189en_US
dc.identifier.urihttps://doi.org/10.1016/j.jestch.2020.01.006
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4892
dc.identifier.volume23en_US
dc.identifier.wosWOS:000514548800016en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier - Division Reed Elsevier India Pvt Ltden_US
dc.relation.ispartofEngineering Science and Technology-An International Journal-Jestechen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectButterflyen_US
dc.subjectDeep learningen_US
dc.subjectClassificationen_US
dc.subjectResNeten_US
dc.subjectTransfer learningen_US
dc.titleAutomatic identification for field butterflies by convolutional neural networksen_US
dc.typeArticleen_US

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