| contributor author | Kamari, Mirsalar | |
| contributor author | Ham, Youngjib | |
| date accessioned | 2026-08-20T21:34:52Z | |
| date available | 2026-08-20T21:34:52Z | |
| date copyright | 2025/07/21 | |
| date issued | 2025 | |
| identifier other | JCEMD4.COENG-16355.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4314685 | |
| description abstract | AbstractThe construction industry has seen a surge in the use of vision-based methods to enhance
project management by addressing quality control, progress monitoring, and safety
risks. However, existing vision-based frameworks typically operate under a ...Practical ApplicationsThe construction industry increasingly utilizes camera-equipped devices, such as smartphones
and drones, to capture extensive visual data, including images and videos, from jobsites.
This data are analyzed using artificial ... | |
| publisher | American Society of Civil Engineers | |
| title | Advancing 3D Object Detection and Segmentation in Construction Jobsites Using an Open Vocabulary Approach | |
| type | Journal Article | |
| journal volume | 151 | |
| journal issue | 10 | |
| journal title | Journal of Construction Engineering and Management | |
| identifier doi | 10.1061/JCEMD4.COENG-16355 | |
| journal fristpage | 04025141-1 | |
| journal lastpage | 04025141-19 | |
| page | 19 | |
| tree | Journal of Construction Engineering and Management:;2025:;Volume ( 151 ):;issue: 010 | |
| contenttype | Fulltext | |