Class Attendance System

dc.contributor.author	Muhammad Bilal, Salman Shabbir and Maira Arshad
dc.date.accessioned	2025-09-23T12:09:56Z
dc.date.available	2025-09-23T12:09:56Z
dc.date.issued	2024
dc.description.abstract	This documentation presents the development, design, working, and implementation of an AI-based attendance system which is sophisticated technology to take attendance in schools, colleges, universities, and offices. In many institutes or organizations RFID biometrics, Punch cards, and traditional sheets are used for attendance but they time time-consuming, have potential inaccuracies, easy to mistake and it’s very difficult to verify attendance by administration. Our proposed model is AI and ML based which takes attendance automatically and is flexible for largescale in which we use Computer Vision, Neural Networks, OpenCV, Convolutional Neural Networks (CNN), Facial Recognition, MTCNN and VGG16. In it, the camera can capture images and match these images with trained images given to the model in the database and store attendance in the database or in an Excel sheet. Our project has a user-friendly interface and ensures data privacy.
dc.identifier.uri	https://escholar.umt.edu.pk/handle/123456789/6771
dc.language.iso	en
dc.publisher	UMT, Lahore
dc.title	Class Attendance System
dc.type	Thesis

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