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@article{162740,
        author = {Garlapati Karthik and R.Arthi and K.Abhinaya Reddy and N.Srinitha Reddy},
        title = {Road Accident Detection Model Using Deep Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {10},
        pages = {910-914},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=162740},
        abstract = {In this fast-paced world, the number of deaths due to accident is growing at an expeditious rate. Major reasons for these accidents are rash driving, drowsiness, drunken driving, carelessness, etc. An indicator of survival rates after detecting accidents is the time between the occurrence of accidents and the advent of medical care to the victim. The rapid growth of technology has made everything more facile and this advancement in technology additionally increased accidents. Due to this delayed medical attention, the accident victims might die as well. As a solution to these problems, we introduce a system that detects road accidents and will provide an alert message to the most proximate control room immediately. The camera module of the system is deployed in accident-prone areas. Whenever an accident occurs, it will detect the accident and immediately report about it to the nearby control room. The working of the system is based on deep learning techniques that use convolutional neural networks. By utilizing this system, many people can be saved from death. },
        keywords = {Deep learning, image processing, neural networks.},
        month = {},
        }