Student's attendance management using deep facial recognition
Tarik Hachad, Abdelalim Sadiq, Fadoua Ghanimi · 2020
Managing student attendance is a repetitive and time-consuming task for both teachers and school administrators. For this reason, we thought of automating this task by deploying the recent advances of machine learning. In this article, we propose an attendance management system based on facial detection and recognition. The classroom is continuously photographed using a camera. An in-depth analysis is applied to the captured images to detect and extract the facial features of the students. Next, a pattern recognition model predicts their identities. The results of the experiment validate the proposed architecture. The process of marking the students' attendance is maintained without any human intervention.