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W3C Strategic Highlights September 2019 This report was prepared for the September 2019 W3C Advisory Committee Meeting (W3C Member link). See the accompanying W3C Fact Sheet — September 2019. For the previous edition, see the April 2019 W3C Strategic Highlights. For future editions of this repo... Read more

# Intelligence traffic monitoring system ### About Due to a huge number of vehicles ,very busy road and parking which may not be possible manually as a human being, tends to get fatigued due to monotonous nature of the job and they cannot keep track of the vehicles when there are multiple vehicl... Read more

Leverage machine learning to aid in the tagging of drivable ways (i.e. roads) in OpenStreetMap.

The goal of this project is to provide object detection and information on environment model on traffic activity which helps autonomous vehicles or surveillance systems. Computer vision is an essential component for autonomous scars. Accurate detection of vehicles, street buildings, pedestrians, ... Read more

The "Driver Coach" system is based on a camera, sensors and machine learning algorithms. It monitors car driver behaviour and provides feedback to improve road safety. The system can be part of a larger Road Safety ECO system sharing data between driver and organisations (Smart City).

Machine Learning Roadmap: From Novice to Pro

The project utilizes the power of deep machine learning to detect and classify the surrounding environment hazards for vehicle. This includes passers-by, traffic signs and other vehicles in road. The implemented system streams live scene of vehicle traffic augmented with hazards alerts detected t... Read more

# Intellifotainment assist” – Smart HMI for passenger cars To run the program, download all files and save them in the same directory. After that, simply run 'Master.py' in the terminal. At the moment, the program will only run in linux based systems. # The Idea Infotainment systems have com... Read more

It is intended to detect damage to road images taken by a camera. For this, deep learning technology, a subspace of machine learning, and Convolutional Neural Networks (CNN), one of the most popular types of deep neural networks, are used. The TensorFlow library is trained through the Ssd Incepti... Read more