LUD-YOLO: A novel lightweight object detection network for unmanned aerial vehicle
Guizhou University · Huazhong University of Science and Technology · +7 more institutions
Abstract
• A Lightweight Object Detection Network called LUD-YOLO for UAVs. • A new feature fusion pattern has been proposed to address the degradation of feature interaction. • Proposing a novel feature extraction module to improve inference speed. • The lightweight adjustment of the model overcomes the shortcomings in UAV applications. • Comparisons demonstrate that LUD-YOLO is better than other 10 competitors. Autonomous execution of tasks by unmanned aerial vehicles (UAVs) relies heavily on object detection. However, object detection in most images presents challenges such as complex backgrounds, small targets, and obstructions. Additionally, the limited computing speed and memory of the UAV processor affects the…
Citation impact
- FWCI
- 25.95
- Percentile
- 100%
- References
- 37
Authors
5- QFQingsong Fan
Guizhou University, Huazhong University of Science and Technology
- YLYiting LiCorresponding
Guizhou University of Finance and Economics, Guizhou University
- MDMuhammet DeveciCorresponding
Naval Academy, Western Caspian University, Imperial College London
- KZKaiyang Zhong
Zhejiang University
- SKSeifedine Kadry
Lebanese American University, Middle East University
Topics & keywords
- Computer science
- Artificial intelligence
- Object (grammar)
- Object detection
- Computer vision
- Pattern recognition (psychology)