| contributor author | Li, Linchao | |
| contributor author | Cui, Xiaodong | |
| contributor author | Wang, Junzheng | |
| contributor author | Jin, Hao | |
| contributor author | Xu, Hongbin | |
| date accessioned | 2026-08-20T10:38:44Z | |
| date available | 2026-08-20T10:38:44Z | |
| date copyright | 2025/11/17 | |
| date issued | 2026 | |
| identifier other | JCEMD4.COENG-16807.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4311067 | |
| description abstract | AbstractTunnel construction environments pose significant challenges for real-time monitoring
due to narrow spaces, poor lighting, and high densities of personnel and machinery.
This paper proposes an enhanced deep-learning framework for automated ... | |
| publisher | American Society of Civil Engineers | |
| title | Automated Tracking of Worker and Heavy Equipment on Tunnel Construction Sites: Deep-Learning Framework | |
| type | Journal Article | |
| journal volume | 152 | |
| journal issue | 2 | |
| journal title | Journal of Construction Engineering and Management | |
| identifier doi | 10.1061/JCEMD4.COENG-16807 | |
| journal fristpage | 04025237-1 | |
| journal lastpage | 04025237-16 | |
| page | 16 | |
| tree | Journal of Construction Engineering and Management:;2026:;Volume ( 152 ):;issue: 002 | |
| contenttype | Fulltext | |
