Browsing by Author "SHAHNEWAZ SIDDIQUE"

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    DISTRACTED DRIVER DETECTION USING MACHINE LEARNING AND DEEP LEARNING
    (North South University, 2020-04-30) Ali Shahan; Enamul Haque; SHAHNEWAZ SIDDIQUE; 1520317042; 1531422642
    One of the main reason of most car accidents is distracted driving, which is the act of driving while engaging in other such as texting, talking on the phone, etc. activities. Activities of that nature distract the driver from paying attention to the road. These distractions in turn compromise the safety of the driver, passengers, bystanders and others in other vehicles. 7,796 deaths due to accidents in 2018, a report of Bangladesh Passengers Welfare Association said at least 7,796 people were killed and 15,980 were injured in 6,048 accidents. The United States Department of Transportation states that one in five car accidents are caused by distracted drivers. This work looks at various images of distracted drivers taken from people performing different actions, some of which can be deemed as distracting whilst behind the wheel of a car. A mixture of various neural network is used in order to more accurately predict what activity a driver is being distracted by.