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dc.contributor.authorPark, Sangyoon
dc.contributor.authorJu, Sungha
dc.contributor.authorHong, Jiwan
dc.contributor.authorHeo, Joon
dc.date.accessioned2026-08-20T21:27:43Z
dc.date.available2026-08-20T21:27:43Z
dc.date.copyright2026/02/24
dc.date.issued2026
dc.identifier.otherJCCEE5.CPENG-7153.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314492
dc.description.abstractAbstractDeep learning-based point cloud semantic segmentation methods require extensive labeled datasets, which involve a tedious manual labeling process. Although synthetic-based approaches have been developed to reduce labeling cost, they must be ...
dc.publisherAmerican Society of Civil Engineers
dc.titleAutomated and Fast Point Cloud Labeling Method for Training Data Augmentation Using Scan-versus-BIM Approach
dc.typeJournal Article
dc.journal.volume40
dc.journal.issue3
dc.journal.titleJournal of Computing in Civil Engineering
dc.identifier.doi10.1061/JCCEE5.CPENG-7153
dc.journal.fristpage04026026-1
dc.journal.lastpage04026026-19
dc.page19
dc.treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 003
dc.contenttypeFulltext


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