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 …

To resolve the issues of a deep backbone network, a large model, slow reasoning speed on
a mobile terminal, low detection accuracy for small targets and difficulties detecting and …

Aiming at solving the problem of missed detection and low accuracy in detecting traffic signs
in the wild, an improved method of YOLOv8 is proposed. Firstly, combined with the …

The current driverless technology has great security risks. The traffic sign recognition
technology equipped in the roof sensor is easily affected by light and occlusion, resulting in …

A new lightweight traffic sign detection algorithm based on YOLOv4 has been proposed to
address the time-consuming issue of existing algorithms when training more parameters …

As the core technology in the field of intelligent transportation, traffic sign detection and
recognition play a significant role in unmanned driving, high-precision map navigation, and …

Detecting traffic signs is an essential task for intelligent and connected vehicles. In this study,
a modified model based on the method of You Only Look Once (YOLO) is proposed for …

Automobile intelligence is the trend for modern automobiles, of which environment
perception is the key technology of intelligent automobile research. For autonomous …

In the deep learning algorithm, YOLOv4 and Faster R-CNN have achieved excellent target
detection performance. To improve the real-time detection of small targets in traffic signs, this …

With the development of automatic driving technology, traffic sign detection has become a
very important task. However, it is a challenging task because of the complex traffic sign …