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dc.contributor.authorKamari, Mirsalar
dc.contributor.authorHam, Youngjib
dc.date.accessioned2026-08-20T21:34:52Z
dc.date.available2026-08-20T21:34:52Z
dc.date.copyright2025/07/21
dc.date.issued2025
dc.identifier.otherJCEMD4.COENG-16355.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314685
dc.description.abstractAbstractThe 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 ...
dc.publisherAmerican Society of Civil Engineers
dc.titleAdvancing 3D Object Detection and Segmentation in Construction Jobsites Using an Open Vocabulary Approach
dc.typeJournal Article
dc.journal.volume151
dc.journal.issue10
dc.journal.titleJournal of Construction Engineering and Management
dc.identifier.doi10.1061/JCEMD4.COENG-16355
dc.journal.fristpage04025141-1
dc.journal.lastpage04025141-19
dc.page19
dc.treeJournal of Construction Engineering and Management:;2025:;Volume ( 151 ):;issue: 010
dc.contenttypeFulltext


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