Automated Student Attendance System Using Face Recognition

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dc.authorscopusid57220815419
dc.authorscopusid57220814479
dc.authorscopusid23980961100
dc.contributor.authorAkay, E.O.
dc.contributor.authorCanbek, K.O.
dc.contributor.authorOniz, Y.
dc.date.accessioned2024-07-18T20:17:10Z
dc.date.available2024-07-18T20:17:10Z
dc.date.issued2020
dc.description4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 -- 22 October 2020 through 24 October 2020 -- -- 165025en_US
dc.description.abstractIn this study, an automated attendance taking system is developed and implemented. Two different face detection algorithms, namely Histogram of Oriented Gradients and Haar-Cascade algorithms, are applied and their performances are compared. Deep learning based on convolutional neural networks (CNNs) is employed for the identification of the students in the classroom. Furthermore, a mask checking feature is also included as a measure against the Covid-19 pandemic. A graphical user interface (GUI) system is designed using Python. © 2020 IEEE.en_US
dc.identifier.doi10.1109/ISMSIT50672.2020.9255052
dc.identifier.isbn9781728190907
dc.identifier.scopus2-s2.0-85097684445en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/ISMSIT50672.2020.9255052
dc.identifier.urihttps://hdl.handle.net/11411/6422
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 - Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAutomated Attendanceen_US
dc.subjectComputer Visionen_US
dc.subjectFace Recognitionen_US
dc.titleAutomated Student Attendance System Using Face Recognitionen_US
dc.typeConference Objecten_US

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