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http://dx.doi.org/10.6109/jkiice.2021.25.3.490

Face-Mask Detection with Micro processor  

Lim, Hyunkeun (Department of Computer Engineering, Paichai University)
Ryoo, Sooyoung (Department of Computer Engineering, Paichai University)
Jung, Hoekyung (Department of Computer Engineering, Paichai University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.25, no.3, 2021 , pp. 490-493 More about this Journal
Abstract
This paper proposes an embedded system that detects mask and face recognition based on a microprocessor instead of Nvidia Jetson Board what is popular development kit. We use a class of efficient models called Mobilenets for mobile and embedded vision applications. MobileNets are based on a streamlined architechture that uses depthwise separable convolutions to build light weight deep neural networks. The device used a Maix development board with CNN hardware acceleration function, and the training model used MobileNet_V2 based SSD(Single Shot Multibox Detector) optimized for mobile devices. To make training model, 7553 face data from Kaggle are used. As a result of test dataset, the AUC (Area Under The Curve) value is as high as 0.98.
Keywords
TinyML; Maixduino; Micropython; MobileNet; Mask detection;
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