TAKING STUDENT ATTENDANCE USING FACIAL RECOGNITION
Face Recognition Student Attendance allows for the real-time monitoring of students’ everyday attendance. high definition face biometrics are used to monitor student attendance. one such application is face recognition, a subset of machine learning that makes use of deep learning methods. The presen...
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2022
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Online Access: | http://utpedia.utp.edu.my/id/eprint/24594/1/TAKING%20STUDENT%20ATTENDANCE%20USING%20FACIAL%20RECOGNITION.pdf http://utpedia.utp.edu.my/id/eprint/24594/ |
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oai:utpedia.utp.edu.my:245942023-06-16T02:18:48Z http://utpedia.utp.edu.my/id/eprint/24594/ TAKING STUDENT ATTENDANCE USING FACIAL RECOGNITION SHAMSUL HISHAM, ALIF AIMAN T Technology (General) Face Recognition Student Attendance allows for the real-time monitoring of students’ everyday attendance. high definition face biometrics are used to monitor student attendance. one such application is face recognition, a subset of machine learning that makes use of deep learning methods. The present systems for tracking attendance take a long time. Records of attendance that are manually recorded are prone to error. Accuracy and real-time can be the main features that differentiate the existing project with this project. This project’s major concern and goal is to address these aspects. 2022-09 Final Year Project NonPeerReviewed text en http://utpedia.utp.edu.my/id/eprint/24594/1/TAKING%20STUDENT%20ATTENDANCE%20USING%20FACIAL%20RECOGNITION.pdf SHAMSUL HISHAM, ALIF AIMAN (2022) TAKING STUDENT ATTENDANCE USING FACIAL RECOGNITION. [Final Year Project] (Submitted) |
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T Technology (General) SHAMSUL HISHAM, ALIF AIMAN TAKING STUDENT ATTENDANCE USING FACIAL RECOGNITION |
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Face Recognition Student Attendance allows for the real-time monitoring of students’ everyday attendance. high definition face biometrics are used to monitor student attendance. one such application is face recognition, a subset of machine learning that makes use of deep learning methods. The present systems for tracking attendance take a long time. Records of attendance that are manually recorded are prone to error. Accuracy and real-time can be the main features that differentiate the existing project with this project. This project’s major concern and goal is to address these aspects. |
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Final Year Project |
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SHAMSUL HISHAM, ALIF AIMAN |
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SHAMSUL HISHAM, ALIF AIMAN |
author_sort |
SHAMSUL HISHAM, ALIF AIMAN |
title |
TAKING STUDENT ATTENDANCE USING FACIAL RECOGNITION |
title_short |
TAKING STUDENT ATTENDANCE USING FACIAL RECOGNITION |
title_full |
TAKING STUDENT ATTENDANCE USING FACIAL RECOGNITION |
title_fullStr |
TAKING STUDENT ATTENDANCE USING FACIAL RECOGNITION |
title_full_unstemmed |
TAKING STUDENT ATTENDANCE USING FACIAL RECOGNITION |
title_sort |
taking student attendance using facial recognition |
publishDate |
2022 |
url |
http://utpedia.utp.edu.my/id/eprint/24594/1/TAKING%20STUDENT%20ATTENDANCE%20USING%20FACIAL%20RECOGNITION.pdf http://utpedia.utp.edu.my/id/eprint/24594/ |
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1769845319117307904 |
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13.214268 |