FaceTrace: Automated Facial Recognition Attendance System

FaceTrace: Automated Facial Recognition Attendance System

Salman Khurshid, Aamir Ansari, Ayush Verma, Piyush Pratap Singh, Manju Khari
DOI: 10.4018/979-8-3693-1186-8.ch011
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Abstract

A person's attendance is crucial in determining their presence and attentiveness. An organisation, college, or a school daily requires attendance to monitor its employees and students. When done the old-fashioned way, managing attendance can take much time. This work focuses on a user-friendly and reliable method of keeping track of attendance considering the times. This chapter proposes an Android-based online attendance application, FaceTrace, that can be used to record attendance. It facilitates paperless attendance. It is an automated and user-friendly facial recognition attendance system designed to automate attendance tracking using facial recognition. With this application, the students can mark their attendance by scanning their faces into the camera, while teachers can take manual attendance whenever necessary. The application generates detailed attendance reports in PDF format. It eliminates the need for manual attendance taking regular paper attendance saving valuable. It is accessible from any device, making it an ideal solution for educational institutions of all sizes.
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Literature Survey

This section provides a deep insight into the previous works related to facial recognition and highlights the background process of face recognition technology. Facial recognition technology, powered by machine learning algorithms and neural networks enables fast and accurate identification of individuals. In the context of this paper, it automates the attendance management process. The facial recognition technology provides improved efficiency, accuracy, and security in various sectors, contributing to streamlined operations and enhanced user experiences.

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