Face Mask Detection by using Optimistic Convolutional Neural Network

被引:22
|
作者
Suresh, K. [1 ]
Palangappa, M. B. [1 ]
Bhuvan, S. [1 ]
机构
[1] Amrita Vishwa Vidyapeetham, Amrita Sch Arts & Sci, Dept Comp Sci, Mysore, Karnataka, India
关键词
Face Mask Detection; Convolutional Neural Networks (CNNs); Kaggle Datasets; Public Safety; COVID-19; OpenCV;
D O I
10.1109/ICICT50816.2021.9358653
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
COVID-19 pandemic has rapidly increased health crises globally and is affecting our day-to-day lifestyle. A motive for survival recommendations is to wear a safe facemask, stay protected against the transmission of coronavirus. By wearing a facemask, the most effective preventive care must be taken against COVID-19. Monitoring manually if the individuals are wearing facemask correctly and to notify the victim in public and crowded areas is a difficult task. This paper approaches a simplified way to achieve facemask detection and notifying the individual if not wearing facemask. Using Kaggle datasets, the proposed system/model is trained and examined. The system runs in real-time and detects if an individual face has facemask if not then notify the individual personally through text message. The mask is extracted from real-time faces in public and is fed as an input into convolutional neural network (CNN).
引用
收藏
页码:1084 / 1089
页数:6
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