Masked Face Recognition Attendance System Using A Modified Convolutional Neural Network

Main Article Content

Jun Jie How
Shing Chiang Tan
Kim Soon Liew

Abstract

In this paper, a masked face recognition based attendance system is developed by modifying a version 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. The 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.


 


Manuscript received: 6 Mar 2022 | Revised: 6 May 2022 | Accepted: 21 Jun 2022 | Published: 8 Jul 2022

Article Details

How to Cite
How, J. J., Tan, S. C., & Liew, K. S. . (2022). Masked Face Recognition Attendance System Using A Modified Convolutional Neural Network. International Journal on Robotics, Automation and Sciences, 4, 23–29. https://doi.org/10.33093/ijoras.2022.4.4
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Articles

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(Accessed: 5 May 2022)