FRMAI: A Robust System Design for Student Attendance Handling Mechanism using Face Recognition Model and Artificial Intelligence Logic

The chore of keeping up with daily activities while also keeping accurate attendance records is not an easy one. Traditional roll call requires time and energy, and it’s easy for a proxy to sit in. The technique that follows uses facial recognition to keep track of student attendance. This project’s overarching objective is to create a facial recognition-based attendance procedure for educational institutions that can replace or significantly improve upon the rudimentary systems already in place and increase the system’s efficiency and effectiveness. We built this system using deep learning methods, namely the histogram of directed gradient approach for detecting faces in pictures and the corresponding deep learning method for computing and comparing feature facial characteristics of students for recognition. Functionality and user satisfaction were evaluated according to standard software engineering metrics, yielding an overall mean very satisfactory grade of 3.5.

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Publication Details

Published
2024-09-18
DOI
https://doi.org/10.1109/icosec61587.2024.10722689
Citations
1
Primary Topic
Smart Systems and Machine Learning
Type
article
Field-Weighted Citation Impact
0.35
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article

FRMAI: A Robust System Design for Student Attendance Handling Mechanism using Face Recognition Model and Artificial Intelligence Logic

Kurakula Sai Satish, V. Reddy, M. Chowdhary, Srinija Gatram
1 citations
Smart Systems and Machine Learning
0.35
article

FRMAI: A Robust System Design for Student Attendance Handling Mechanism using Face Recognition Model and Artificial Intelligence Logic

Kurakula Sai Satish, V. Reddy, M. Chowdhary, Srinija Gatram
article en
1 citations

Abstract

The chore of keeping up with daily activities while also keeping accurate attendance records is not an easy one. Traditional roll call requires time and energy, and it’s easy for a proxy to sit in. The technique that follows uses facial recognition to keep track of student attendance. This project’s overarching objective is to create a facial recognition-based attendance procedure for educational institutions that can replace or significantly improve upon the rudimentary systems already in place and increase the system’s efficiency and effectiveness. We built this system using deep learning methods, namely the histogram of directed gradient approach for detecting faces in pictures and the corresponding deep learning method for computing and comparing feature facial characteristics of students for recognition. Functionality and user satisfaction were evaluated according to standard software engineering metrics, yielding an overall mean very satisfactory grade of 3.5.

Amrita Vishwa Vidyapeetham (IN)
Openalex Percentile: Top 37%
Smart Systems and Machine Learning
0.35
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FRMAI: A Robust System Design for Student Attendance Handling Mechanism using Face Recognition Model and Artificial Intelligence Logic — Kurakula Sai Satish, V. Reddy, et al. · (2024) | TGRS Research Map | TGRS