Real Time Face Mask Detection Using Mobilenetv2 Algorithm
M. Dhilsath Fathima, Ramamoorthy Hariharan, Prashant Kumar Singh, Praveen Kumar, S. R. Ramya, M. Seeni Syed Raviyathu Ammal · 2023
The coronavirus outbreak is a life-threatening event that has resulted in a huge number of deaths and causing health concerns. Governments all across the world were forced to impose lockdowns due to the coronavirus’s quick spread stop infection from spreading further. Wearing a face mask publicly and at work considerably reduces the chance of transmission during this epidemic, according to several health reports. When they leave the house, however, the majority of individuals do not use masks. According to a study, 80 percent of people do not use masks appropriately. The proposed MobileNetV2 algorithm, which builds a fast and accurate face mask identification model, is used in this study to provide a solution to the face mask detection problem. MobileNetV2 is the cutting-edge object identification algorithm to find the face mask in real-time. The proposed method efficiently handles object detection and contributes to high object detection accuracy of 99.6 percent and decreased object detection time.