Segmentation of wood cell in cross-section using deep convolutional neural networks

dc.contributor.authorErgun, Halime
dc.date.accessioned2024-02-23T14:34:44Z
dc.date.available2024-02-23T14:34:44Z
dc.date.issued2021
dc.departmentNEÜen_US
dc.description.abstractFiber and vessel structures located in the cross-section are anatomical features that play an important role in identifying tree species. In order to determine the microscopic anatomical structure of these cell types, each cell must be accurately segmented. In this study, a segmentation method is proposed for wood cell images based on deep convolutional neural networks. The network, which was developed by combining two-stage CNN structures, was trained using the Adam optimization algorithm. For evaluation, the method was compared with SegNet and U-Net architectures, trained with the same dataset. The losses in these models trained were compared using IoU (Intersection over Union), accuracy, and BF-score measurements on the test data. The automatic identification of the cells in the wood images obtained using a microscope will provide a fast, inexpensive, and reliable tool for those working in this field.en_US
dc.identifier.doi10.3233/JIFS-211386
dc.identifier.endpage7456en_US
dc.identifier.issn1064-1246
dc.identifier.issn1875-8967
dc.identifier.issue6en_US
dc.identifier.scopus2-s2.0-85122031428en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage7447en_US
dc.identifier.urihttps://doi.org/10.3233/JIFS-211386
dc.identifier.urihttps://hdl.handle.net/20.500.12452/15733
dc.identifier.volume41en_US
dc.identifier.wosWOS:000731754900112en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIos Pressen_US
dc.relation.ispartofJournal Of Intelligent & Fuzzy Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectImage Segmentationen_US
dc.subjectFiber-Vesselen_US
dc.subjectMicroscopic Wood Cellsen_US
dc.subjectDeep Convolutional Neural Networksen_US
dc.titleSegmentation of wood cell in cross-section using deep convolutional neural networksen_US
dc.typeArticleen_US

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