Akay, E.O.Canbek, K.O.Oniz, Y.2024-07-182024-07-1820209781728190907https://doi.org/10.1109/ISMSIT50672.2020.9255052https://hdl.handle.net/11411/64224th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 -- 22 October 2020 through 24 October 2020 -- -- 165025In 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.eninfo:eu-repo/semantics/closedAccessAutomated AttendanceComputer VisionFace RecognitionConference Object2-s2.0-8509768444510.1109/ISMSIT50672.2020.9255052N/A