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• W3204709868 abstract "COVID-19 has dramatically changed people’s daily life. Wearing masks is considered as a simple but effective way to defend the spread of the epidemic. Hence, a real-time and accurate mask wearing detection system is important. In this paper, a deep learning-based mask wearing detection system is developed to help people defend against the terrible epidemic. The system consists of three important functions, which are image detection, video detection and real-time detection. To keep a high detection rate, a deep learning-based method is adopted to detect masks. Unfortunately, according to the suddenness of the epidemic, the mask wearing dataset is scarce, so a mask wearing dataset is collected in this paper. Besides, to reduce the computational cost and runtime, a simple online and real-time tracking method is adopted to achieve video detection and monitoring. Furthermore, a function is implemented to call the camera to real-time achieve mask wearing detection. The sufficient results have shown that the developed system can perform well in the mask wearing detection task. The precision, recall, mAP and F1 can achieve 86.6%, 96.7%, 96.2% and 91.4%, respectively." @default.
• W3204709868 created "2021-10-11" @default.
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• W3204709868 date "2021-09-30" @default.
• W3204709868 modified "2023-09-26" @default.
• W3204709868 title "A Mask Wearing Detection System Based on Deep Learning" @default.
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• W3204709868 doi "https://doi.org/10.33851/jmis.2021.8.3.159" @default.
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