Digi Attendance – Artificial Intelligence Based Attendance System

Authors

  • Wasil Khan Student, School of Engineering and Technology, Sharda University, Greater Noida, India
  • Abrar Shafi Bhat Student, School of Engineering and Technology, Sharda University, Greater Noida, India
  • Kusumlata Assistant Professor, School of Engineering and Technology, Sharda University, Greater Noida, India

Keywords:

student attendance system,, Multi-Task Cascaded Convolutional Neural Networks (MTCNN), deep metric learning, Facenet

Abstract

Attendance of the students is much essential in the education system. To mark and store the attendance of student’s different ways can be adopted like by calling the students one by one, signatures on the attendance sheet. The process has different drawbacks, like time consuming. we proposed a web-based student attendance system that incorporates face recognition as a solution to this problem. In the proposed system, to detect faces in images we use, Multi-Task Cascaded Convolutional Neural Networks (MTCNN), to extract features from image Facenet is used, and SVM is used as classifier. So, the computer can identify faces. According to the results of the experiments, the system resulted in recognizing faces and marking their attendance. By this process keeping the record of attendance becomes very easy for educational institutes.

Downloads

Download data is not yet available.

Downloads

Published

19-04-2023

Issue

Section

Articles

How to Cite

[1]
W. Khan, A. S. Bhat, and Kusumlata, “Digi Attendance – Artificial Intelligence Based Attendance System”, IJRAMT, vol. 4, no. 4, pp. 43–47, Apr. 2023, Accessed: Nov. 21, 2024. [Online]. Available: https://journals.ijramt.com/index.php/ijramt/article/view/2659