Face Mask Detection with Temperature Check
i-Manager's Journal on Information Technology
; 11(1):1-9, 2022.
Article
in English
| ProQuest Central | ID: covidwho-2030577
ABSTRACT
The coronavirus (COVID-19) pandemic is causing a worldwide health catastrophe, so according to the World Health Organization (WHO), wearing masks in public is an effective safety method. The COVID-19 pandemic has forced governments around the world to impose quarantines to prevent transmission of the virus. According to reports, wearing masks in public does reduce the threat of transmission of the virus. An efficient and cost-effective way to use Artificial Intelligence (AI) to create a secure environment in a manufacturing environment. A hybrid model for using a deep and classic face mask detection device will be proposed. The face mask detection dataset includes the mask, and without mask photos, it uses the Open-Source Computer Vision Library (OpenCV) to detect faces in real-time from the stay circulation through the webcam. It uses the dataset to build a computer vision COVID-19 face mask detector using Python, OpenCV, TensorFlow, and Keras. Using computer vision and deep learning, the goal is to understand whether a character in a picture or video stream is wearing a mask or not using computer vision and deep learning.
Technology: Comprehensive Works; Temperature Check; Python; OpenCV; Convolution Neural Network; COVID-19; Machine Learning; Datasets; Deep learning; Pandemics; Masks; Viruses; Video data; Computer vision; Catastrophic wear; Viral diseases; Artificial intelligence; Coronaviruses; Disease transmission
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
I-Manager's Journal on Information Technology
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS