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Distracted Driver Detection - using machine learning neural network model

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THE PROJECT FOCUSSES ON DRIVER DISTRACTION ACTIVITY WHICH CAN LEAD TO ACCIDENTS USING CNN MODEL OF MACHINE LEARNING.
OUR GOAL IS TO BUILD A HIGH ACCURACY MODEL THAT CAN IDENTIFY ACTIVITIES LIKE DRIVER YAWNING, TEXTING ON PHONE AND TALKING ON MOBILE.
THE INPUT OF OUR MODEL IS - IMAGES OF DRIVER TAKEN IN THE CAR COLLECTED FROM ANY AVAILABLE DATASET FROM THE INTERNET.
THESE  IMAGES CAPTURED ARE PRE-PROCESSED TO GET INPUT VECTOR, THEN USING CNN CLASSIFIER AN OUTPUT IS PREDICTED LEADING TO A TYPE OF DISTRACTION ACTIVITY THAT DRIVERS ARE CONDUCTING.