Abstract Machine learning (ML) plays the core function to intellectualize the transportation
systems. Recent years have witnessed the advent and prevalence of deep learning which …

This paper capitalizes on the increasingly high relevance gained by data-intensive
technologies in the development of intelligent transportation system, which calls for the …

Classifying traffic signs is an indispensable task for autonomous driving systems. Depending
on the country, traffic signs possess a wide variability in their visual appearance making it …

Road sign recognition is a driver support function that can be used to notify and warn the
driver by showing the restrictions that may be effective on the current stretch of road …

Object detection acts as an essential part in a wide range of measurement systems in traffic
management, urban planning, defense, agriculture, and so on. Convolutional Neural …

This article presents a computer vision system for real-time detection and robust recognition
of speed limit signs, specially designed for intelligent vehicles. First, a new segmentation …

Deep learning methods are being increasingly applied in transport studies, while the
methods require modellers to go through a try-and-error model tuning process particularly …

Traffic signs are a key constituent of the road network and prove to be very useful for
warning and guiding the drivers. In intelligent transport systems, traffic sign recognition …

Initially, the traffic-sign recognition was done using the conventional image processing
techniques which are sluggish and can cause fatal delays in real-world implementations …

The paper describes an approach towards road sign detection and recognition system. The
model consists of two parts: localization and recognition. First one is responsible for the …