FACE MASK DETECTION USING MTCNN AND MOBILENETV2
Published in International Research Journal of Engineering and Technology (IRJET) , Volume 8 Issue 3 March 2021, 2021
Recommended citation: Vansh Gupta , Rajeev Rajput, 2021, FACE MASK DETECTION USING MTCNN AND MOBILENETV2, International Research Journal of Engineering and Technology (IRJET) , Volume 8 Issue 3 March 2021 https://www.irjet.net/volume8-issue3
Abstract
The COVID-19 pandemic is causing a worldwide wellbeing emergency so the viable security technique is wearing a face cover in open regions as indicated by the World Health Organization (WHO). As the world recuperates from the pandemic and plans to get back to a condition of routineness, there is an influx of tension among all people, particularly the individuals who expect to continue face to face movement. Studies have demonstrated that wearing a face veil essentially diminishes the danger of viral transmission just as gives a feeling of assurance. Notwithstanding, it isn’t plausible to physically follow the execution of this strategy. Technology holds the key here. We will use the dataset to build a COVID-19 face mask detector with computer vision using Python, OpenCV, and Tensor Flow, and Keras. Our goal is to create a model that can detect face masks in crowded public places.
Status - Published
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