Face Recognition for Classroom Attendance Based on Convolutional Neural Network

Authors

  • Suhel Sayyad Annasaheb Dange College of Engineering and Technology Ashta https://orcid.org/0000-0002-5208-0829
  • Anis Mulla Annasaheb Dange College of Engineering and Technology Ashta
  • Nikita Gote Annasaheb Dange College of Engineering and Technology Ashta
  • Pranita Bhosale Annasaheb Dange College of Engineering and Technology Ashta
  • Pallavi Yadav Annasaheb Dange College of Engineering and Technology Ashta
  • Ishika Adsul Annasaheb Dange College of Engineering and Technology Ashta

Keywords:

Face Recognition, Classroom Attendance, Image Processing

Abstract

Marking the attendance of every student manually is a very inconvenient and time consuming task. Our system is based on deep learning architecture to prevent these issues. The automatic attendance system is based on image processing and consists of face recognition, automatically marking a student’s attendance. Face recognition is well studied in computer vision, but it remains unsolved because of pose changes, varying light conditions, and occlusions. Also, teachers spend more time marking each student’s attendance manually. The criteria of minimum time for students in the classroom will be set by the instructor. Our system will monitor the attendance of students through face recognition. As per the timetable’s time and minimum time set by the instructor, student attendance will be marked and stored in the database which will be accessible to   the admin.

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References

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Published

25.12.2023

How to Cite

Sayyad, S. ., Mulla , A. ., Gote, N. ., Bhosale, P. ., Yadav, P. ., & Adsul, I. . (2023). Face Recognition for Classroom Attendance Based on Convolutional Neural Network. International Journal of Intelligent Systems and Applications in Engineering, 12(1), 474–479. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3945

Issue

Vol. 12 No. 1 (2024)

Section

Research Article

License

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