- Tytuł:
- Real-time face mask detection in mass gatherings to reduce Covid-19 spread
- Autorzy:
-
Soner, Swapnil
Litoriya, Ratnesh
Khatri, Ravi
Hussain, Ali Asgar
Pagrey, Shreyas
Kushwaha, Sunil Kumar - Powiązania:
- https://bibliotekanauki.pl/articles/27314233.pdf
- Data publikacji:
- 2023
- Wydawca:
- Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
- Tematy:
-
Covid
machine learning
face mask detection
Deep Learning - Opis:
- The Covid 19 (coronavirus) pandemic has become one of the most lethal health crises worldwide. This virus gets transmitted from a person by respiratory droplets when they sneeze or when they speak. According to leading and well‐known scientists, wearing face masks and maintain‐ ing six feet of social distance are the most substantial protections to limit the virus’s spread. In the proposed model we have used the Convolutional Neural Network (CNN) algorithm of Deep Learning (DL) to ensure efficient real‐time mask detection. We have divided the system into two parts—1. Train Face Mask Detector 2. Apply Face Mask Detector—for better understanding. This is a real‐ time application that is used to discover or detect the person who is wearing a mask at the proper position or not, with the help of camera detection. The system has achieved an accuracy of 99% after being trained with the dataset, which contains around 1376 images of width and height 224×224 and also gives the alarm beep message after the detection of no mask or improper mask usage in a public place.
- Źródło:
-
Journal of Automation Mobile Robotics and Intelligent Systems; 2023, 17, 1; 51--58
1897-8649
2080-2145 - Pojawia się w:
- Journal of Automation Mobile Robotics and Intelligent Systems
- Dostawca treści:
- Biblioteka Nauki
Artykuł