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@article{154790,
        author = {Muskan Chourasia and Monika Bhandakkar and Laxmi Thakare and Dnyaneshwari Mendhe and Nehal Mane and C.U.Chauhan},
        title = {Helmet Detection on Construction site using AI},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {12},
        pages = {446-450},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154790},
        abstract = {The ordinary security defensive cap wearing affirmation is simply established on the overshadowing, shape, surface and various characteristics of the image, which is remarkably affected by the external environment, and has the issue of unstable affirmation accuracy. Considering the above issues, this paper focuses on the affirmation procedure for power improvement worker's security head defender subject to man-made intellectual ability development. Resulting to pre-handling the improvement actually taking a look at picture, for instance, becoming Gray and denoising, the advancement work force in the ID picture are found, that is to say, in light of perceiving the improvement staff district, the head position of the advancement personnel is found, finally the prosperity defensive cap wearing affirmation is recognized by using YOLO computation. The re-establishment results show that the typical affirmation precision is 95.2%, the affirmation sway is consistent and has extraordinary generosity.},
        keywords = {Helmet detection, AI system, Deep learning, Accident preventions.},
        month = {},
        }