| contributor author | Wang, Jiehui | |
| contributor author | Chen, Ziyang | |
| contributor author | Ueda, Tamon | |
| contributor author | Dai, Jian-Guo | |
| date accessioned | 2026-08-20T21:28:45Z | |
| date available | 2026-08-20T21:28:45Z | |
| date copyright | 2026/03/18 | |
| date issued | 2026 | |
| identifier other | JCCEE5.CPENG-7482.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314522 | |
| description abstract | AbstractWith the rapid advancement of deep learning, automated inspection of reinforced concrete
(RC) structures has become increasingly viable. However, existing models are typically
task-specific, limiting their utility across diverse scenarios. This ...Practical ApplicationsThis study presents a new, all-in-one artificial intelligence framework designed to
help engineers and inspectors quickly and accurately identify multiple types of damage
in concrete structures. Unlike many existing tools that can ... | |
| publisher | American Society of Civil Engineers | |
| title | Development and Evaluation of a Task-Adaptive and Hierarchical Deep Learning Framework for Multitype Damage Detection in Reinforced Concrete Structures | |
| type | Journal Article | |
| journal volume | 40 | |
| journal issue | 4 | |
| journal title | Journal of Computing in Civil Engineering | |
| identifier doi | 10.1061/JCCEE5.CPENG-7482 | |
| journal fristpage | 04026032-1 | |
| journal lastpage | 04026032-18 | |
| page | 18 | |
| tree | Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 004 | |
| contenttype | Fulltext | |