Citation

Abdul Haris, Muhamad Amin Husni and Lim, Sin Liang (2021) Neural Network Facial Authentication for Public Electric Vehicle Charging Station. Journal of Engineering Technology and Applied Physics, 3 (1). pp. 17-21. ISSN 26828383

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Abstract

This study is to investigate and compare the facial recognition accuracy performance of Dlib ResNet against a K-Nearest Neighbour (KNN) classifier. Particularly when used against a dataset from an Asian ethnicity as Dlib ResNet was reported to have an accuracy deficiency when it comes to Asian faces. The comparisons are both implemented on the facial vectors extracted using the Histogram of Oriented Gradients (HOG) method and use the same dataset for a fair comparison. Authentication of a user by facial recognition in an electric vehicle (EV) charging station demonstrates a practical use case for such an authentication system.

Item Type:	Article
Uncontrolled Keywords:	Machine learning, neural network, computer vision, facial recognition, classifier
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication. Including telegraphy, telephone, radio, radar, television
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Mr. MUHAMMAD AZRUL MOSRI
Date Deposited:	07 Aug 2024 03:24
Last Modified:	07 Aug 2024 03:24
URII:	http://shdl.mmu.edu.my/id/eprint/12753

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