Automated Student Attendance System Using Face Recognition
E. Omer Akay, K. Oguz Canbek, Yeşim Öniz · 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) · 2020
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.