Effectiveness of different machine learning algorithms in road extraction from UAV-based point cloud

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dc.contributor.authorBiçici, Serkan
dc.date.accessioned2024-12-05T08:20:59Z
dc.date.available2024-12-05T08:20:59Z
dc.date.issued2024
dc.departmentAÇÜ, Mühendislik Fakültesi, Harita Mühendisliği Bölümüen_US
dc.description.abstractThis study presents the evaluation of seven different machine learning (ML) models to classify road surface from point cloud. The study begins with converting two-dimensional images collected from unmanned aerial vehicles (UAV) flights to three-dimensional (3D) point cloud. Seven different ML models, namely, Generalized Linear Model, Linear Discriminant Analysis, Robust Linear Discriminant Analysis, Random Forest, Support Vector Machine with Linear Kemel, Linear eXtreme Gradient Bossting, and eXtreme Gradient Boosting, were developed under different training samples. Finally, road surface were classified from 3D point cloud using developed ML models. To assess the performance of the ML models, manually extracted road surfaces were compared with the ones obtained from ML models. Generalized Linear Model produces the most accurate classification results in a shorter processing time. On the other hand, Linear eXtreme Gradient Boosting and eXtreme Gradient Boosting models produce less accurate road classification in a longer processing time. The classification accuracies of other ML models are between these.
dc.identifier.doi10.1007/978-3-031-54376-0_6
dc.identifier.endpage74en_US
dc.identifier.issn2367-3370
dc.identifier.scopusqualityQ4
dc.identifier.startpage65en_US
dc.identifier.urihttp://dx.doi.org/10.1007/978-3-031-54376-0_6
dc.identifier.urihttps://hdl.handle.net/11494/5110
dc.identifier.volume938en_US
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofLecture Notes in Networks and Systems
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/embargoedAccessen_US
dc.subject3Den_US
dc.subjectML-Modelen_US
dc.subjectPoint-Clouden_US
dc.subjectRoaden_US
dc.subjectUAVen_US
dc.titleEffectiveness of different machine learning algorithms in road extraction from UAV-based point clouden_US
dc.typeConference Object

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