The detection of traffic signs is easily affected by changes in the weather, partial occlusion,
and light intensity, which increases the number of potential safety hazards in practical …

The timely and accurate identification of traffic signs plays a significant role in realizing the
autonomous driving of vehicles. However, the size of traffic signs accounts for a low …

This study proposes an embedded traffic sign detection system, YOLOV5-MCBS, based on
an enhanced YOLOv5 algorithm. This system aims to mitigate the impact of traditional target …

Fast and accurate detection of traffic signs is crucial for the development of intelligent
transportation systems. To address the issue of false detection and missing detection of …

As one of the key technologies of intelligent vehicles, traffic sign detection is still a
challenging task because of the tiny size of its target object. To address the challenge, we …

The ability to recognize traffic signs is a critical skill for safe driving, as traffic signs provide
drivers with essential information about the road conditions, potential hazards, speed limits …

To improve safe driving and reduce the mental fatigue of drivers, accurate and fast access to
traffic sign guidance information in road scenes is needed. This work proposes a traffic sign …

With the progress of advanced driver assistance systems (ADAS), the development of
assisted driving technologies is becoming more and more important for vehicle subsystems …

Autonomous vehicle technology is evolving with deep learning. Traffic sign recognition
informs the driver of necessary information when the driver does not recognize the traffic …

Traffic sign recognition can provide road information assessment and real-time safety early
warning for safe driving of vehicles. The YOLOv4 model was adopted for traffic sign …