8 papers · 1 filter
YOLO-LLTS: Real-Time Low-Light Traffic Sign Detection via Prior-Guided Enhancement and Multibranch Feature Interaction
Ziyu Lin, Yunfan Wu, Yuhang Ma +5
Traffic sign detection is essential for autonomous driving and Advanced Driver Assistance Systems (ADAS). However, existing methods struggle to address the challenges of poor image…
Lane Departure Accident Prevention in Foggy Conditions: A Prior-Guided Dynamic Feature Fusion Transformer Framework for Real-Time Lane Detection
Ronghui Zhang, Yuhang Ma, Tengfei Li +9
Lane departure accident prevention plays a critical role in enhancing road safety, and lane detection is a core technology to achieve this goal, especially under complex weather co…
WTEFNet: Real-Time Low-Light Object Detection for Advanced Driver Assistance Systems
Hao Wu, Junzhou Chen, Ronghui Zhang +4
Object detection is a cornerstone of environmental perception in advanced driver assistance systems(ADAS). However, most existing methods rely on RGB cameras, which suffer from sig…
ABCDWaveNet: Advancing Robust Road Ponding Detection in Fog through Dynamic Frequency-Spatial Synergy
Ronghui Zhang, Dakang Lyu, Tengfei Li +7
Road ponding presents a significant threat to vehicle safety, particularly in adverse fog conditions, where reliable detection remains a persistent challenge for Advanced Driver As…
YOLO-TS: Real-Time Traffic Sign Detection with Enhanced Accuracy Using Optimized Receptive Fields and Anchor-Free Fusion
Junzhou Chen, Heqiang Huang, Ronghui Zhang +4
Ensuring safety in both autonomous driving and advanced driver-assistance systems (ADAS) depends critically on the efficient deployment of traffic sign recognition technology. Whil…
AGSENet: A Robust Road Ponding Detection Method for Proactive Traffic Safety
Ronghui Zhang, Shangyu Yang, Dakang Lyu +5
Road ponding, a prevalent traffic hazard, poses a serious threat to road safety by causing vehicles to lose control and leading to accidents ranging from minor fender benders to se…