| contributor author | Meda, Dhathri | |
| contributor author | Ahmed, Mohammed Mustafa | |
| contributor author | Kalapatapu, Prafulla | |
| contributor author | Pasupuleti, Venkata Dilip Kumar | |
| date accessioned | 2026-08-20T21:25:00Z | |
| date available | 2026-08-20T21:25:00Z | |
| date copyright | 2025/06/14 | |
| date issued | 2025 | |
| identifier other | JCCEE5.CPENG-6686.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314416 | |
| description abstract | AbstractIn infrastructure monitoring, manual inspections and conventional computer vision
techniques have long been the standard for detecting structural damage. Nevertheless,
these approaches are frequently constrained by their reliance on human ... | |
| publisher | American Society of Civil Engineers | |
| title | Enhanced Structural Damage Detection, Segmentation, and Quantification Using Computer Vision and Deep Learning | |
| type | Journal Article | |
| journal volume | 39 | |
| journal issue | 5 | |
| journal title | Journal of Computing in Civil Engineering | |
| identifier doi | 10.1061/JCCEE5.CPENG-6686 | |
| journal fristpage | 04025066-1 | |
| journal lastpage | 04025066-15 | |
| page | 15 | |
| tree | Journal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 005 | |
| contenttype | Fulltext | |
