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All Journal International Journal of Integrated Science and Technology
Omkar S. Gaikwad
Student, Dept. of Information Technology, Aissms Ioit, Pune, Maharashtra, India.
Computer Science & IT Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Social Sciences

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Facial Recognition Attendance Monitoring System using Deep Learning Techniques M.A Thalor; Omkar S. Gaikwad
International Journal of Integrated Science and Technology Vol. 2 No. 1 (2024): January 2024
Publisher : MultiTech Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59890/ijist.v2i1.1290

Abstract

The Facial Recognition Attendance Monitoring System employing Deep Learning Techniques represents a cutting-edge application of artificial intelligence in educational and corporate environments. The implementation of a Facial Recognition System can aid in identifying or verifying a person's identity from a digital image. Accurate attendance records are vital to classroom evaluation. However, manual attendance tracking can result in errors, missed students, or duplicate entries. The adoption of the Face Recognition-based attendance system could help eliminate these shortcomings. This innovative approach involves utilizing a camera to capture input images, detecting faces using algorithms such as Haarcascade, Eigen values, support vector machines, or the Fisher face algorithm, verifying the faces against a database of student profiles, and marking attendance in an Excel sheet. The use of OpenCV, an open-source computer vision library, ensures the efficient
Co-Authors M.A Thalor