Traffic sign detection is a crucial element of advanced driver assistance systems (ADAS) for
environmental perception. However, challenges persist in the detection of small-scale …

Traffic sign detection is a challenging task. Although existing deep learning techniques have
made great progress in detecting traffic signs, there are still many unsolved challenges. We …

Traffic sign detection is an important topic in autonomous driving and intelligent
transportation, as it is widely applied in real-life scenarios to detect crucial road information …

Traffic sign detection and recognition in the wild is a challenging task. Existing techniques
are often incapable of detecting small or occluded traffic signs because of the scale variation …

This paper cater to the problem of traffic sign detection, and proposes an improved
backbone network module C2Net, which uses an improved bidirectional Res2Net to …

Traffic signs are one of the most important information that guide cars to travel, and the
detection of traffic signs is an important component of autonomous driving and intelligent …

Automatic detection and classification of traffic signs have become an essential asset in the
visual system of autonomous vehicles and self-driving cars. Recently, vision transformers …

Most existing traffic sign detection models suffer from high computational complexity and
superior performance but cannot be deployed on edge devices with limited computational …

To solve the problem that existing traffic signs are not easily detected leading to low
detection performance due to their small sizes and external factors such as weather …

In the actual traffic environment, it is highly susceptible to interference from external factors
such as illumination intensity and deformation of traffic signs, resulting in low detection rate …