Context: YOLO (You Look Only Once) is an algorithm based on deep neural networks with
real-time object detection capabilities. This state-of-the-art technology is widely available …

With the advancement of intelligent driving technology, researchers are paying more and
more attention to the identification of traffic signs. Although a detection method of traffic signs …

In this paper, we aim at the traffic sign detection and recognition in complex road conditions.
We proposed a deep model for traffic sign detection and recognition. There are a few …

The detection of multi-class small objects poses a significant challenge in the field of
computer vision. While the original YOLOv5 algorithm is more suited for detecting full-scale …

The progress of technology in our current world continues to advance each day, benefiting
human beings in various ways. One significant development in recent time is the emergency …

Traffic sign recognition plays a crucial role in the intelligent vehicle's environment perception
system. However, due to varying weather conditions, illumination, and complicated …

Foreign objects easily attach to the transmission lines because of the various laying
methods and the complex, changing environment. They have a significant impact on the …

In real scenarios, accurate and real‐time detection of traffic signs is of great significance to
the automatic driving system. To meet the requirements of detection accuracy and speed, a …

A street scene in a city can be split into several different objects. The primary focus of this
paper is on developing an autonomous recognition system for detecting and recognising …

Traffic sign detection plays a vital role in assisted driving and automatic driving. YOLOv5, as
a one-stage object detection solution, is very suitable for Traffic sign detection. However, it …