REVIEW LIMIT COVID-19 USING FACIAL MASK DETECTION USING BOOSTED CNN IN SMART CITY NETWORK

Author Name: 1. Manoj Kumar 2. Vijai Pratap Tiwari

Volume/Issue: 02/01

Country: India

DOI NO.: 08.2020-25662434 DOI Link: https://www.doi-ds.org/doilink/07.2021-96363556/UIJIR

Affiliation:

1. Professor Of Lakshmi Narain College of Technology & Science, Bhopal, India
2. Student, Lakshmi Narain College of Technology & Science, Bhopal, India

ABSTRACT

The Corona virus COVID-19 causes the global health epidemic, while the OPP wears a WHO face mask in public places (WHO). Governments all over the world have implemented programmes to monitor virus transmission in response to the COVID-19 pandemic. According to studies, the initiative has significantly reduced the risk of transmission. AI is a cost-effective and reliable way to create a secure production environment. To detect face mask, a hybrid model using a deeper and conventional machine learning mix is used. OpenCV detects face pictures in real time from live streams using our webcam, mask filter, and disguised video. The data set is used to build a COVID-19 facial mask detector using Python, OpenCV, Flow, and Keras. Our goal is to see whether using a computer view and a video or picture stream for a person wearing a face mask is advantageous.

Key words: Covid-19, Facial Mask Detection, BOOSTED CNN