Automated Student Attendance System Using Face Recognition

Abstract

In 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.