Fast-ICA Based Lane Detection Method for Autonomous Vehicles

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dc.authorscopusid57215410023en_US
dc.authorscopusid57220339538en_US
dc.authorwosidABF-9873-2020
dc.authorwosidABF-8916-2020
dc.contributor.authorDogru, Hasibe Busra
dc.contributor.authorZengin, Aydin Tarik
dc.date.accessioned2025-07-03T23:14:51Z
dc.date.available2025-07-03T23:14:51Z
dc.date.issued2022en_US
dc.departmentMühendislik ve Doğa Bilimleri Fakültesien_US
dc.descriptionProceedings of the 2022 26th International Conference Electronics / Institute of Electrical and Electronics Engineers Inc. -- ISBN:978-166548321-6 -- DOI: 10.1109/IEEECONF55059.2022.9810405 -- 2022.en_US
dc.description.abstractLane detection is an important process in autonomous vehicle systems. Noise in the image, such as object shadows and terminating lane lines, make lane detection difficult. This study proposes a Convolutional Neural Network architecture with a dimension reduction method that has not been used before in lane detection. The proposed method has been tested with the open-source TuSimple dataset. The results showed that the proposed Fast-Independent Component Analysis based model training improved performance in lane detection and reduced the mean percent error by 42.2%.en_US
dc.identifier.citationDogru, H. B., & Zengin, A. T. (2022, June). Fast-ICA Based Lane Detection Method for Autonomous Vehicles. In 2022 26th International Conference Electronics (pp. 1-6). IEEE.en_US
dc.identifier.doi10.1109/IEEECONF55059.2022.9810405
dc.identifier.endpage6en_US
dc.identifier.isbn978-166548321-6
dc.identifier.orcid0000-0002-5944-260Xen_US
dc.identifier.orcid0000-0002-0860-4509en_US
dc.identifier.scopus2-s2.0-85135053197en_US
dc.identifier.scopusqualityN/A
dc.identifier.startpage1en_US
dc.identifier.urihttps://doi.org/10.1109/IEEECONF55059.2022.9810405
dc.identifier.urihttps://hdl.handle.net/20.500.12436/7779
dc.identifier.wosWOS:000853483400009
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorDogru, Hasibe Busra
dc.institutionauthorZengin, Aydin Tarik
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Incen_US
dc.relation.ispartof26th International Conference Electronicsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAutonomous vehiclesen_US
dc.subjectDeep learningen_US
dc.subjectIndependent component analysisen_US
dc.subjectLane detectionen_US
dc.titleFast-ICA Based Lane Detection Method for Autonomous Vehiclesen_US
dc.typeConference Object
dspace.entity.typePublication

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