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@article{151771,
        author = {Abhay Singh Rana and Umang Sahu and Aryan Srivastava and Yugank},
        title = {Social Distancing detector},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {903-906},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151771},
        abstract = {Computer vision and machine learning techniques have been used in order to detect object in an image or in a video. Using these techniques the social distancing followed by the people can be evaluated which is really a necessity for the people nowadays, so that they can avoid or protect themselves from the ongoing coronavirus. It is an application of computer vision and deep learning.Computer Vision is a branch of computer that works like an eye of the computer that can recognize and also understand images and activities while deep learning is a function of artificial intelligence that try to mimic the working of human brain.Using highly accurate object detection-algorithms and methods such as R-CNN, Fast-RCNN, Faster-RCNN, Darknet and fast yet highly accurate ones like SSD and YOLO4.we can detect each and every human in image by the area object in an highlighted rectangular boxes and identify whether or not they are following social distancing or not. This also includes the accuracy of each method for the identification of the objects. It also shows the number of people violating the social distancing rule at a given moment or a frame.},
        keywords = {Computer Vision, Deep Learning, Social distancing detection, Machine learning},
        month = {},
        }