Automatic Face Mask Detection Using Deep Learning

被引:1
作者
Anderson, Stephanie [1 ]
Veeravenkatappa, Suma [1 ]
Pola, Priyanka [1 ]
Pouriyeh, Seyedamin [1 ]
Han, Meng [1 ]
机构
[1] Kennesaw State Univ, Dept Informat Technol, Marietta, GA 30060 USA
来源
26TH IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (IEEE ISCC 2021) | 2021年
关键词
COVID-19; Convolutional Neural Networks; Deep Learning; Face Mask Detection; Machine Learning;
D O I
10.1109/ISCC53001.2021.9631409
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 shook the entire world with its highly infectious transmission and death rate. As per CDC guidelines, wearing a mask can effectively reduce the spread of COVID-19 and create a protective barrier against the virus until the efficacy of currently available vaccines reaches 100% and the majority of people get vaccinated. Wearing masks is highly recommended almost everywhere, in schools, stores, movies, etc. to prevent the spread of this virus, however, monitoring people to see whether they wear masks is not an easy task. As a result, different face mask detection models were proposed. In this paper, we introduce a face mask detection model using deep learning. We have taken into consideration three different categories to train our model, Mask, No Mask, and Incorrect Mask. The proposed model has achieved 96% accuracy.
引用
收藏
页数:4
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