| dc.contributor.author | Zhao, Wenzhuo | |
| dc.contributor.author | Li, Ke | |
| dc.contributor.author | Liu, Gang | |
| dc.contributor.author | Chen, Bin | |
| dc.contributor.author | Fan, Mingyu | |
| dc.contributor.author | Yin, Shuohui | |
| dc.date.accessioned | 2026-08-20T10:41:10Z | |
| dc.date.available | 2026-08-20T10:41:10Z | |
| dc.date.copyright | 2026/04/07 | |
| dc.date.issued | 2026 | |
| dc.identifier.other | JCEMD4.COENG-17156.pdf | |
| dc.identifier.uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4311120 | |
| dc.description.abstract | AbstractCrack detection is a critical task in the diagnosis and assessment of bridge health.
Currently, most crack detection methods concentrate solely on a single aspect (segmentation,
object detection, or classification) and are incapable of fulfilling ... | |
| dc.publisher | American Society of Civil Engineers | |
| dc.title | A Three-Stage Intelligent Crack Detection Method for Concrete Bridges Based on Deep Neural Networks | |
| dc.type | Journal Article | |
| dc.journal.volume | 152 | |
| dc.journal.issue | 6 | |
| dc.journal.title | Journal of Construction Engineering and Management | |
| dc.identifier.doi | 10.1061/JCEMD4.COENG-17156 | |
| dc.journal.fristpage | 04026067-1 | |
| dc.journal.lastpage | 04026067-14 | |
| dc.page | 14 | |
| dc.tree | Journal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 006 | |
| dc.contenttype | Fulltext | |
