Automated System for Attendance Tracking and Management Using Face Recognition

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Year : July 30, 2024 at 12:47 pm | [if 1553 equals=””] Volume :11 [else] Volume :11[/if 1553] | [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] : 02 | Page : –

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Abhijeet More, Anushka Kadam, Aditi Bhopale, Siddhant Kamble, Sumit Nalawade,

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  1. Assistant Professor, Student, Student, Student, Student Department Computer Engineering, Pillai Hoc college of Engineering and technology (Mumbai University) Rasayani, Department Computer Engineering, Pillai Hoc college of Engineering and technology (Mumbai University) Rasayani, Department Computer Engineering, Pillai Hoc College Of Engineering And Technology (Mumbai University) Rasayani, Department Computer Engineering, Pillai Hoc College Of Engineering And Technology (Mumbai University) Rasayani, Department Computer Engineering, Pillai Hoc College Of Engineering And Technology (Mumbai University) Rasayani Maharashtra, Maharashtra, Maharashtra, Maharashtra, Maharashtra India, India, India, India, India
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Abstract

nA camera is used by an attendance tracking system that uses facial recognition to snap photos of people. After that, a computer program analyzes these images and uses facial feature analysis to identify specific individuals. Subsequently, the system can ascertain whether or not the identified individuals are present by comparing the identified individuals to a database that already has information about known individuals. This technology can be used to expedite the process of collecting attendance and reduce the likelihood of errors resulting from human error in a variety of settings, including offices, industries, and educational institutions. A more complete outcome for overseeing participation might be gotten by joining facial acknowledgment with different innovations, for example, time and participation observing programming. It recognizes deep learning algorithms and utilizes the newest technologies to make attendance more intelligent. This outcomes in the production of a framework that can distinguish and perceive the essences of the understudies signed up for the class. The area of the individuals head that is situated in the frontal region first is the face. Specifically, it is the region that encompasses the top of the head, the bottom of the jawline, and the area between the ears. Facial recognition is one of the biometric measurements that should be required for this system. This concept allows it to do all the tasks of a sophisticated attendance tracking system in half the time it would take a human to complete them. This idea predicts that student data and attendance tracking technology will be successful.

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Keywords: Attendance, Face Identification, OpenCV, Training and Recognition, Database

n[if 424 equals=”Regular Issue”][This article belongs to Journal of Image Processing & Pattern Recognition Progress(joipprp)]

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[/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in Journal of Image Processing & Pattern Recognition Progress(joipprp)][/if 424][if 424 equals=”Conference”]This article belongs to Conference [/if 424]

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How to cite this article: Abhijeet More, Anushka Kadam, Aditi Bhopale, Siddhant Kamble, Sumit Nalawade. Automated System for Attendance Tracking and Management Using Face Recognition. Journal of Image Processing & Pattern Recognition Progress. July 30, 2024; 11(02):-.

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How to cite this URL: Abhijeet More, Anushka Kadam, Aditi Bhopale, Siddhant Kamble, Sumit Nalawade. Automated System for Attendance Tracking and Management Using Face Recognition. Journal of Image Processing & Pattern Recognition Progress. July 30, 2024; 11(02):-. Available from: https://journals.stmjournals.com/joipprp/article=July 30, 2024/view=0

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References

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[if 424 not_equal=””]Regular Issue[else]Published[/if 424] Subscription Review Article

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Volume 11
[if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 02
Received June 24, 2024
Accepted July 16, 2024
Published July 30, 2024

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