Year: 2025
Type: article
Abstract: This study focused on the development and implementation of a facial recognition system for automating student attendance tracking. The system is built using Python, Flask, OpenCV, and face recognition libraries, designed to integrate with the university database. Testing revealed high accuracy and efficiency, allowing real-time recognition and attendance recording. The system presents a scalable and reliable solution for educational institutions looking to automate attendance processes.
Source: MU Journal
Authors: Kasamu, Nzila, Halubanza, Brian
Institution: Mulungushi University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W7219935945