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@article{155774,
        author = {ANURAG and Mansi Gupta and Akshay Kumawat},
        title = {Face Mask Recognition Using Open CV},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {1},
        pages = {1758-1761},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155774},
        abstract = {Corona Virus is a big threat to mankind. In the last few years, COVID-19 pandemic has remarkably affected our day-to-day life affecting the world trade and movements. It is causing a worldwide emergency in healthcare. This virus transmits when people breathe in air contaminated by droplets and small airborne particles containing the virus. The risk of breathing these in is highest when people are in proximity, but they can be inhaled over longer distances, particularly indoors. Transmission can also occur if splashed or sprayed with contaminated fluids in the eyes, nose, or mouth, and, rarely, via contaminated surfaces. Wearing a face mask has become mandatory as World Health Organization (WHO) mentioned it limits the spread of virus. This paper presents a simplified approach to achieve this purpose using some basic deep Learning packages like TensorFlow, Keras, OpenCV. The proposed methodology detects the face from the image/video stream correctly and then identifies if it has a mask on it or not. As a surveillance task performer, it can also detect a face along with a mask in motion.  },
        keywords = {COVID-19, Tensorflow, OpenCV, Face Mask, Image Processing, Computer Vision.},
        month = {},
        }