Deep learning has become a standard approach to machine vision in recent years. Despite
several advances, it requires large amounts of annotated data. Nonetheless, in many …

Traffic sign detection is one of the critical technologies in the field of intelligent transportation
systems (ITS). The difficulty of traffic sign detection mainly lies in detecting small objects in a …

Deep learning has been successfully applied to several problems related to autonomous
driving. Often, these solutions rely on large networks that require databases of real image …

Driving is a complex, continuous, and multitask process that involves driver's cognition,
perception, and motor movements. The way road traffic signs and vehicle information is …

Recent trends in the development of autonomous vehicles focus on real-time processing of
vast amounts of data from various sensors. The data can be acquired using multiple …

Deep learning has developed rapidly and made unprecedented achievements especially in
the field of image cognition, since Alex et al. proposed AlexNet in 2012. This paper focuses …

Real time and accurate traffic sign detection is one of the important technologies to realize
automatic driving and intelligent transportation. Due to the complex background and small …

In this paper we propose a real-time traffic sign recognition algorithm which is robust to the
small-sized objects and can identify all traffic sign categories. Specifically, we present a two …

Advanced Driver Assistance Systems rely on automated traffic sign recognition. Today,
Deep Learning methods outperform other approaches in terms of accuracy and processing …

In this paper, we propose a method for training traffic sign detectors without using actual
images of the traffic signs. The method involves using training images of road scenes that …