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dc.contributor.authorSharif, Haidar
dc.contributor.authorUyaver, Şahin
dc.contributor.authorSharif, Haris Uddin
dc.contributor.authorİnce, İbrahim Furkan
dc.contributor.authorZerdo, Zaid
dc.date.accessioned2021-01-08T21:51:32Z
dc.date.available2021-01-08T21:51:32Z
dc.date.issued2019
dc.identifier.isbn9789811315008
dc.identifier.issn2194-5357
dc.identifier.urihttps://doi.org/10.1007/978-981-13-1501-5_27
dc.identifier.urihttps://hdl.handle.net/20.500.12846/339
dc.descriptionInternational Conference on Emerging Technologies in Data Mining and Information Security, IEMIS 2018, 23 February 2018 through 25 February 2018, , 217929en_US
dc.description.abstractIt is a challenging task to classify heterogeneous geographical features from satellite imagery. This paper addresses 31 straightforward classification algorithms based on predominantly pixels to classify miscellaneous geographical features from satellite imagery. The addressed algorithms can extract and process the features of a large dataset with high-resolution images expeditiously. A total of 606 red-green-blue satellite images of the Bosnian city of Banja Luka are exercised to comprehend their performances for classifying cemeteries, fields, houses, industries, rivers, and trees. The recorded experimental results demonstrate that the best average performance can come into possession of 87%. © Springer Nature Singapore Pte Ltd. 2019.en_US
dc.language.isoengen_US
dc.publisherSpringer Verlagen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleClassification of geographical features from satellite imageryen_US
dc.typeconferenceObjecten_US
dc.relation.journalAdvances in Intelligent Systems and Computingen_US
dc.identifier.volume814en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.contributor.departmentTAÜ, Fen Fakültesi, Enerji Bilimi ve Teknolojileri Bölümüen_US
dc.contributor.institutionauthorUyaver, Şahin
dc.identifier.doi10.1007/978-981-13-1501-5_27
dc.identifier.startpage309en_US
dc.identifier.endpage321en_US
dc.identifier.scopusqualityN/Aen_US


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