Citation

How, Jun Jie and Tan, Shing Chiang and Liew, Kim Soon (2022) Masked Face Recognition Attendance System Using A Modified Convolutional Neural Network. International Journal on Robotics, Automation and Sciences, 4. pp. 23-29. ISSN 2682-860X

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Abstract

n this paper, a masked face recognition based attendance system is developed by modifying aversion of convolutional neural network (CNN).In this regard, a Support Vector Machine is integrated in the CNN to replace its original Softmax classifier to perform the task.T he performance of the modified CNN in recognizing masked faces in a 5-fold cross validation was compared that of other CNNs. The experimental results show high effectiveness of the proposed CNN (i.e. 98.92%) in recognizing masked faces for recording attendance.

Item Type:	Article
Uncontrolled Keywords:	Deep learning, convolutional neural network, support vector machine, masked face images
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75-76.95 Calculating machines
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	22 Jul 2022 01:06
Last Modified:	22 Jul 2022 01:06
URII:	http://shdl.mmu.edu.my/id/eprint/10168

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