distracted-driving-detection
There are 3 repositories under distracted-driving-detection topic.
e-candeloro / Driver-State-Detection
A real time, webcam based, driver attention state detection/monitoring system in Python3 using OpenCV and Mediapipe
Language:Python 136- TelematicsApp-Android
Mobile-Telematics / TelematicsApp-Android
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
Language:Kotlin 65 Abhinav1004 / Distracted-Driver-Detection
Solves a kaggle problem of State Farm Distracted Driver Detection
Language:Jupyter Notebook 54Raj1036 / ML_Distracted_Driver_Detection
This Distracted Driver Detection Project is developed by a group of 5 students as part of "CS 539 Machine Learning" Course
Language:Jupyter Notebook 8hamna-moieez / MachineLearning
Implementation of various ML algorithms and their application to real world problems
Language:Jupyter Notebook 1phoenix-1-2 / Distracted-Driver-Detection
This is a machine learning/neural network model that is used to predict the likelihood of what the driver is doing in the picture.
Language:Jupyter Notebook 1samyak24jain / distracted-driver-detection
Detecting a distracted driver using CNNs.
Language:Jupyter Notebook 1shsarv / Distracted-Driver-Detection
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 the phone - right c3: texting - left c4: talking on the phone - left c5: operating the radio c6: drinking c7: reaching behind c8: hair and makeup c9: talking to passenger
Language:Jupyter Notebook 1ManiKumarReddy35 / Machine-Learning
Contains models implemented from scratch and a project implemented from end-to-end
Language:Jupyter Notebook 0thom22 / Deep-Learning-Approach-for-Advanced-Driver-Assistance-System
This work was supported in part by the MOTIE (Ministry of Trade, Industry & Energy), Republic of Korea, under the Technology Innovation Program, and in part by the MSIT (Ministry of Science and ICT), Republic of Korea, under the Grand ICT Research Center Support Program.For full details, refer the published journal article using the link below.
0