| contributor author | Zhang, Huan | |
| contributor author | Feng, Jinyan | |
| contributor author | Dai, Chenghao | |
| contributor author | Tong, Zhaoxia | |
| date accessioned | 2026-08-20T21:24:54Z | |
| date available | 2026-08-20T21:24:54Z | |
| date copyright | 2025/08/20 | |
| date issued | 2025 | |
| identifier other | JCCEE5.CPENG-6675.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314414 | |
| description abstract | AbstractThis study proposes a novel pavement crack segmentation methodology that integrates
synthetic data sets with unsupervised domain adaptation to address annotation challenges
in pavement crack data sets and enhance segmentation performance. An ...Practical ApplicationsAutomated crack detection plays a crucial role in structural health monitoring by
enhancing speed, precision, and reliability. However, training deep learning models
necessitates a vast amount of labeled real-world data, posing ... | |
| publisher | American Society of Civil Engineers | |
| title | Pavement Crack Segmentation Based on Synthetic Data Sets and Unsupervised Domain Adaptation | |
| type | Journal Article | |
| journal volume | 39 | |
| journal issue | 6 | |
| journal title | Journal of Computing in Civil Engineering | |
| identifier doi | 10.1061/JCCEE5.CPENG-6675 | |
| journal fristpage | 04025100-1 | |
| journal lastpage | 04025100-17 | |
| page | 17 | |
| tree | Journal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 006 | |
| contenttype | Fulltext | |