1 citations · 1 across the 6 of their papers we have counts for
5 papers · 1 filter
YOLO-ROC: A High-Precision and Ultra-Lightweight Model for Real-Time Road Damage Detection
Zicheng Lin, Weichao Pan
Road damage detection is a critical task for ensuring traffic safety and maintaining infrastructure integrity. While deep learning-based detection methods are now widely adopted, t…
YOLO-FireAD: Efficient Fire Detection via Attention-Guided Inverted Residual Learning and Dual-Pooling Feature Preservation
Weichao Pan, Bohan Xu, Xu Wang +4
Fire detection in dynamic environments faces continuous challenges, including the interference of illumination changes, many false detections or missed detections, and it is diffic…
EFA-YOLO: An Efficient Feature Attention Model for Fire and Flame Detection
Weichao Pan, Xu Wang, Wenqing Huan
As a natural disaster with high suddenness and great destructiveness, fire has long posed a major threat to human society and ecological environment. In recent years, with the rapi…
Real-Time Dynamic Scale-Aware Fusion Detection Network: Take Road Damage Detection as an example
Weichao Pan, Xu Wang, Wenqing Huan
Unmanned Aerial Vehicle (UAV)-based Road Damage Detection (RDD) is important for daily maintenance and safety in cities, especially in terms of significantly reducing labor costs.…
DAPONet: A Dual Attention and Partially Overparameterized Network for Real-Time Road Damage Detection
Weichao Pan, Jiaju Kang, Xu Wang +2
Current road damage detection methods, relying on manual inspections or sensor-mounted vehicles, are inefficient, limited in coverage, and often inaccurate, especially for minor da…