Citation

Chong, Lucas Wei Jie and Chong, Siew Chin and Ong, Thian Song (2022) Masked Face recognition Using Support Vector Machine and Convolutional Neural Network. In: 022 10th International Conference on Information and Communication Technology (ICoICT), 2-3 August 2022, Bandung, Indonesia.

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Abstract

This paper proposes a masked face recognition algorithm with the amalgamation of Convolutional Neural Network (CNN) and Support Vector Machine (SVM) to improve the true acceptance rate in face image prediction. Specifically, through the proposed uniform pipeline, CNN is implemented to train the model while SVM is used as a label classification method. Two benchmarked datasets which are the Real World Masked Face Dataset (RMFD) and Labelled Face in The Wild Simulated Masked Face Dataset (LFW-SMFD) are applied in the experiments. The proposed method satisfactorily achieves a 98.39 percent true acceptance rate on RMFD and 94.29 percent on LFW-SMFD which demonstrates its practicality in recognizing unconstrained face images.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Deep-learning , neural network , classification , support vector machine , masked face
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	05 Jan 2023 01:35
Last Modified:	05 Jan 2023 01:35
URII:	http://shdl.mmu.edu.my/id/eprint/10757

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