期刊名称：International Journal of Advances in Engineering and Management
电子版ISSN：2395-5252
出版年度：2022
卷号：4
期号：4
页码：839-841
DOI：10.35629/5252-0404600617
语种：English
出版社：IJAEM JOURNAL
摘要：COVID-19 virus has serious consequences Emergency affecting the health of most people Greater impact in most parts of the world by affecting people's health. Important Effective methods are established by maintaining social distance And the duty of the mask. By wearing a mask, It mainly reduces the risk of broadcast of the disease. We try to present a mix model with a classic model Machine learning algorithms, deep learning recognition. The dataset may or may not have images. A mask that attempts to use OpenCV for real-time detection on a webcam. Because it is essential Wear a face mask in public areas for added safety People, we make sure that such a system is implemented for security and for security reasons. You can also use the same model in a workplace that promises that all employees wear masks During the day. Create using a dataset COVID 19 face mask detector using computer vision, Tensor Flow, Python, Keras. Our main goal is to identify whether a person has a face in an image / video stream whether to mask deep learning. We provide a Machine Learning-based system for detecting improper use of face masks. Our system uses Convolutional Neural Network (CNN) architecture with two stages that can recognize both masked and unmasked faces and is compatible with pre-installed CCTV cameras This will be aid in the tracking of safety contravention, the promotion of face mask use, and the creation of a safe working environments.
关键词：machine learning;face mask;OpenCV;Keras;mobile Net V2
