Face recognition attendance marking using YOLOv3

  • G.Rajkumar, Vaibhav Garg, Anmol Anand, M.Eshasree

Abstract

Attendance management can be a great vexation for any school/ university when it comes to manual entry, as nowadays attendance plays a vital role in performance and quality analysis. This traditional and conventional method is highly time-consuming and prone to error. To overcome this mundane method, next-generation AI and ML systems can be used to automate this process.

This paper proposes an automatic attendance management system by implementing Face Recognition, by using YOLO v3, Principal Component Analysis (PCA) and Convolutional Neural Network (CNN). The system is developed by the desegregation of ubiquitous components for attendance marking using the face recognition technique.

Keywords: YOLO v3, Principal Component Analysis (PCA), Convolutional Neural Network (CNN) and face recognition.

Published
2020-04-24
How to Cite
G.Rajkumar, Vaibhav Garg, Anmol Anand, M.Eshasree. (2020). Face recognition attendance marking using YOLOv3 . International Journal of Advanced Science and Technology, 29(05), 2806 - 2811. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/11389