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@article{155957,
        author = {DR Krishnan Bandyopadhyay and Dr Murigendrayya Hiremath and Vidya T S and Soundarya P and Surabhi S and Bhoomika H J},
        title = {Real time face mask detection using alarm system},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {2},
        pages = {426-430},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155957},
        abstract = {In the context of the COVID-19 epidemic, establishments like the academy square measure in danger of being effectively closed worldwide if the present situation doesn't improve.Coronavirus-2 is a contagious disease that spreads through metabolic process droplets from the diseased person who talk without mask , coughs, or mainly he the person sneezes. This virus catches quickly through close contact with the diseased person or by contact with the infected goods or things. The only way to protect ourselves from COVID-19 appears to be to avoid getting infected with the virus. Preventing infection by using a protective mask that mainly covers the nose and mouth in public areas. Deep Learning has being accepted that its usefulness in image detection and characterization as technology progresses. The study provides additional evidence to use deep learning algorithms for facial recognition and identifies whether or not the subject is wearing a facemask. The dataset gathered consists of 3833 images with a resolution of 224x224 pixels, with a 96% accuracy rate on the trained model's performance. If the person spotted isn't using a facemask, the system develops an amount of time for facemask detection and takes the facial image. This research is useful in preventing virus spread and avoiding eye contact with the virus.},
        keywords = {Alarm System, COVID-19, CNN OpenCV, Raspberry Pi, Tensorflow.},
        month = {},
        }