The Project aims to enhance road safety by utilizing machine learning and computer vision techniques to identify and alert against driver distractions in real-time.
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Updated
Jul 24, 2024 - Jupyter Notebook
The Project aims to enhance road safety by utilizing machine learning and computer vision techniques to identify and alert against driver distractions in real-time.
Computer Vision course project - IIIT Delhi CSE544
Proyecto 1 - Programacion Concurrente Y Paralela
Distracted Driver Classification
A new way to prevent distracted driving.
In this, you are given driver images, each taken in a car with a driver doing something in the car (texting, eating, talking on the phone, makeup, reaching behind, etc). Your goal is to predict the likelihood of what the driver is doing in each picture. The 10 classes to predict are as follows, c0: safe driving c1: texting - right c2: talking on…
Final Group Project for DSO110 Data Science
Detect distracted drivers using a trained CNN
Full-stack mobile application with accountability and assistance features to mitigate the risks of distracted driving.
Bosch Hackathon
This Distracted Driver Detection Project is developed by a group of 5 students as part of "CS 539 Machine Learning" Course
Demo telematics app for React-Native. The application walks you through the telematics SDK integration.
Demo telematics app for Flutter. The application walks you through the telematics SDK integration. The technology is suitable for UBI (Usage-based insurance), shared mobility, transportation, safe driving, tracking, family trackers, drive-coach, and other driving mobile applications
An app which uses open CV to monitor if the driver is alert of asleep, and a state farm dataset trained model which scans for 9 different types of distraction.
PyTorch-based Driver Posture Classification
Zenroad - Open-source telematics app for Android. The application is suitable for UBI (Usage-based insurance), shared mobility, transportation, safe driving, tracking, family trackers, drive-coach, and other driving mobile applications
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