| contributor author | Rostami, Ghodsiyeh | |
| contributor author | Chen, Po-Han | |
| contributor author | Hosseini, Mahdi S. | |
| date accessioned | 2026-08-20T21:27:23Z | |
| date available | 2026-08-20T21:27:23Z | |
| date copyright | 2026/02/06 | |
| date issued | 2026 | |
| identifier other | JCCEE5.CPENG-7090.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314482 | |
| description abstract | AbstractImage-based crack detection algorithms are increasingly in demand in infrastructure
monitoring, as early detection of cracks is of paramount importance for timely maintenance
planning. While deep learning has significantly advanced crack detection ...Practical ApplicationsInspecting infrastructure such as bridges, roads, and buildings is critical to ensure
safety, however, traditional methods are often slow, expensive, and pose safety risks
for workers. As a result, there has been a shift toward using ... | |
| publisher | American Society of Civil Engineers | |
| title | Segment Any Crack: Deep Semantic Segmentation Adaptation for Crack Detection | |
| type | Journal Article | |
| journal volume | 40 | |
| journal issue | 3 | |
| journal title | Journal of Computing in Civil Engineering | |
| identifier doi | 10.1061/JCCEE5.CPENG-7090 | |
| journal fristpage | 04026020-1 | |
| journal lastpage | 04026020-14 | |
| page | 14 | |
| tree | Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 003 | |
| contenttype | Fulltext | |