BL-YOLOv8: An Improved Road Defect Detection Model Based on YOLOv8
Abstract
Road defect detection is a crucial task for promptly repairing road damage and ensuring road safety. Traditional manual detection methods are inefficient and costly. To overcome this issue, we propose an enhanced road defect detection algorithm called BL-YOLOv8, which is based on YOLOv8s. In this study, we optimized the YOLOv8s model by reconstructing its neck structure through the integration of the BiFPN concept. This optimization reduces the model's parameters, computational load, and overall size. Furthermore, to enhance the model's operation, we optimized the feature pyramid layer by introducing the SimSPPF module, which improves its speed. Moreover, we introduced LSK-attention, a dynamic large…
Citation impact
- FWCI
- 41.16
- Percentile
- 100%
- References
- 34
Authors
4- XWXueqiu Wang
Shandong Jianzhu University
- HGHuanbing GaoCorresponding
Shandong Jianzhu University
- ZJZemeng Jia
Shandong Jianzhu University
- ZLZijian Li
Shandong Jianzhu University
Topics & keywords
- Computer science
- Task (project management)
- Kernel (algebra)
- Reduction (mathematics)
- Field (mathematics)
- Object detection
- Feature (linguistics)
- Artificial intelligence
- Sustainable cities and communities