Face Recognition Attendance System

The Face Recognition Attendance System (FRAS) is an advanced biometric authentication technology that automates attendance tracking using facial recognition. Traditional attendance systems, such as manual sign-in sheets or RFID cards, are often inefficient and prone to errors. FRAS eliminates these inefficiencies by utilizing deep learning-based face detection and recognition algorithms to ensure accurate and secure attendance tracking. The system includes key components such as facial enrollment, real-time recognition, attendance logging, and security features to protect biometric data. It enhances accuracy, reduces administrative workload, and prevents fraudulent attendance practices like proxy attendance. This project aims to implement a robust, scalable, and secure face recognition attendance system suitable for educational institutions and corporate environments

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Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2025-03-14
DOI
https://doi.org/10.48175/ijarsct-23734
Primary Topic
Face recognition and analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Face Recognition Attendance System

Mukund D. Patil, Prof. Mohan Mali, Mr. Kaustubh Kathole
International Journal of Advanced Research in Science Communication and Technology
Face recognition and analysis
article

Face Recognition Attendance System

Mukund D. Patil, Prof. Mohan Mali, Mr. Kaustubh Kathole
article en

Abstract

The Face Recognition Attendance System (FRAS) is an advanced biometric authentication technology that automates attendance tracking using facial recognition. Traditional attendance systems, such as manual sign-in sheets or RFID cards, are often inefficient and prone to errors. FRAS eliminates these inefficiencies by utilizing deep learning-based face detection and recognition algorithms to ensure accurate and secure attendance tracking. The system includes key components such as facial enrollment, real-time recognition, attendance logging, and security features to protect biometric data. It enhances accuracy, reduces administrative workload, and prevents fraudulent attendance practices like proxy attendance. This project aims to implement a robust, scalable, and secure face recognition attendance system suitable for educational institutions and corporate environments

International Journal of Advanced Research in Science Communication and Technology
Bharati Vidyapeeth (Deemed to be University) (IN)
Openalex Percentile: Top 96%
Face recognition and analysis
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