In order to solve the problems of low accuracy and slow recognition speed of traffic signs, a
multi-layer and multi-scale convolutional neural network recognition algorithm is proposed …

Aiming at the disadvantages of convolutional neural network in traffic sign recognition, such
as poor real-time performance and high hardware requirements, an improved network …

In the existing algorithms for traffic sign recognition, sometimes the training time is short but
the recognition rate is low, and other times the recognition rate is high but the training time is …

In order to improve the recognition accuracy and recognition speed of traffic signs, a
recognition model based on convolutional neural network with high accuracy and fast speed …

Traffic sign recognition (TSR) is a significance research branch in the field of unmanned
driving, which is very important for driverless driving and is often used to read permanent or …

Considering that most convolutional neural network (CNN) models designed for traffic sign
recognition (TSR) have sacrificed more resources and complicated network model …

As an important part of the unmanned driving system, the detection and recognition of traffic
sign need to have the characteristics of excellent recognition accuracy, fast execution speed …

This paper proposes an efficient deep learning approach for the Traffic sign recognition
system (TSR). TSR plays an essential role in the intelligent transportation system (ITS). TSR …

Abstract System for Traffic Sign Recognition and Classification is significantly important for
especially traffic safety, traffic surveillance, artificial driver services and by all means, for self …

As an important part of intelligent transport system (ITS), road traffic sign recognition (TSR)
system gathers information from real-time video frames and recognizes the content of the …