Development of Face Recognition-Based Attendance System

dc.contributor.authorChukwude, Okechukwu M
dc.contributor.authorSURAJUDEEN-BAKINDE, Nazmat Toyin
dc.contributor.authorZakariyya, Sikiru Olayinka
dc.contributor.authorOgunsakin, Joy B
dc.contributor.authorAkanni, Jimoh
dc.contributor.authorOlayanju, Sunday Akinwale
dc.contributor.authorEhiagwina, Frederick O
dc.date.accessioned2023-09-19T08:13:21Z
dc.date.available2023-09-19T08:13:21Z
dc.date.issued2023-05
dc.description.abstractLecture attendance management is usually tedious, and time-consuming and may be prone to errors or manipulations when done manually. Hence, in this work, a web application called RollCall was developed and tested, for use by both students and lecturers in the Faculty of Engineering at the University of Ilorin as a model to manage attendance. The system manages attendance by allowing the lecturers to create courses, and take and retrieve attendance records for the courses created. Student functionalities include uploading their face data, enrolling for courses, and retrieving attendance records for the courses in which they enrolled. Attendance is marked through face recognition technology implemented with Python, OpenCV and Sci-kit Learn. The web interface was implemented using HTML5, Twitter Bootstrap CSS framework and JavaScript. The findings revealed that RollCall effectively streamlined attendance management, making it easier for both students and lecturers to keep track of attendance records. The web application is user-friendly and enhances the overall academic experience by improving the accuracy and efficiency of attendance management.en_US
dc.identifier.issn2736-089X
dc.identifier.urihttps://slujst.com.ng/index.php/jst/issue/view/10
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/11761
dc.language.isoenen_US
dc.publisherFaculty of Natural and Applied Sciences (FNAS) and the Faculty of Computing and Information Technology (FCIT), Sule Lamido University, Kafin Hausa, Jigawa State, Nigeriaen_US
dc.subjectFace Recognition, Class Attendance, OpenCV, Pythonen_US
dc.titleDevelopment of Face Recognition-Based Attendance Systemen_US
dc.typeArticleen_US

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
362-Article Text-1895-1-10-20230404.pdf
Size:
811.11 KB
Format:
Adobe Portable Document Format
Description:
Main article
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:

Collections