Face Recognition Attendance System Using Deep Neural Network

Wang, Tack Kuan (2019) Face Recognition Attendance System Using Deep Neural Network. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

The project proposes facial recognition method to replace the conventional attendance system. This project provides a stress-free way to record the attendance in school and workplace. By using unique biometric information on human’s face, deceitful action in taking attendance can be prevented. With the advancement of Deep Neural Network, face recognition can be done in a timely fashion, thus making the application of face recognition in attendance system possible. Other than continue improving the facial recognition accuracy of Deep Neural Network, a web-based graphical user interface (GUI) that can greatly help in boosting up the user experience of first responder in the handling of attendance taking event is proposed in this project. After detecting a person’s face, the characteristics of the face would be used to compare with the data stored in database via the Deep Neural Network. On matched result, the system will automatically record the attendance of the individual. Attendance information can be viewed back easily with the interactive GUI.

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