A Deep Learning Model for Face Mask Detection

被引：0

作者：

Abd El-Aziz, A. A. ^{[2
]}

Azim, Nesrine A. ^{[2
]}

Mahmood, Mahmood A. ^{[1
,2
]}

Alshammari, Hamoud ^{[1
]}

机构：

[1] Jouf Univ, Fac Comp & Informat Sci, Dept Informat Syst, Sakakah, Saudi Arabia

[2] Cairo Univ, Fac Grad Studies Stat Res, Dept Informat Syst & Technol, Cairo, Egypt

来源：

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY | 2021年 / 21卷 / 10期

关键词：

Face mask; Convolution neural network; deep learning; TensorFlow;

D O I：

10.22937/IJCSNS.2021.21.10.13

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Corona Virus is a big threat to humanity. Now, the whole world is struggling to reduce the spread of Corona virus. Wearing masks is one of the practices that help to control the spread of the virus according to the world health organization. However, ensuring all people wear facemask is not an easy task. In this paper, we propose a simple and effective model for real-time monitoring using the convolution neural network to detect whether an individual wears a face mask or not. The model is trained, validated, tested upon two datasets. Corresponding to dataset 1, the accuracy of the model was 95.77% and, it was 94.58% for dataset 2.

引用

页码：101 / 106

页数：6

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