| contributor author | Cui, Minxing | |
| contributor author | Du, Yanliang | |
| contributor author | Wu, Difei | |
| contributor author | Sun, Lijun | |
| contributor author | Yan, Yu | |
| date accessioned | 2026-08-20T21:28:54Z | |
| date available | 2026-08-20T21:28:54Z | |
| date copyright | 2026/06/09 | |
| date issued | 2026 | |
| identifier other | JCCEE5.CPENG-7693.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314526 | |
| description abstract | AbstractThe application of deep learning to ground penetrating radar (GPR) detection of urban
road subsurface defects is often limited by the scarcity of real-world data and high
computational costs. To address this, we propose a novel framework that ... | |
| publisher | American Society of Civil Engineers | |
| title | Addressing Data Scarcity in GPR Road Defect Detection: A Novel Framework Combining Stable Diffusion and Efficient GCP-YOLO | |
| type | Journal Article | |
| journal volume | 40 | |
| journal issue | 5 | |
| journal title | Journal of Computing in Civil Engineering | |
| identifier doi | 10.1061/JCCEE5.CPENG-7693 | |
| journal fristpage | 04026073-1 | |
| journal lastpage | 04026073-17 | |
| page | 17 | |
| tree | Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 005 | |
| contenttype | Fulltext | |
