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dc.contributor.authorLei, Xiaoming
dc.contributor.authorSun, Mengjin
dc.contributor.authorDong, You
dc.contributor.authorFrangopol, Dan M.
dc.date.accessioned2026-08-20T21:20:24Z
dc.date.available2026-08-20T21:20:24Z
dc.date.copyright2025/07/21
dc.date.issued2025
dc.identifier.otherJBENF2.BEENG-7638.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314312
dc.description.abstractAbstract Traditional structural inspection methods, while effective, often fall short in terms of efficiency, coverage, and consistency, thereby highlighting the need for innovative approaches. This paper presents a novel vision-based framework for ...
dc.publisherAmerican Society of Civil Engineers
dc.titlePanoramic Vision–Driven Deep Learning Framework for Structural Inspection and Condition Assessment
dc.typeJournal Article
dc.journal.volume30
dc.journal.issue10
dc.journal.titleJournal of Bridge Engineering
dc.identifier.doi10.1061/JBENF2.BEENG-7638
dc.journal.fristpage04025061-1
dc.journal.lastpage04025061-15
dc.page15
dc.treeJournal of Bridge Engineering:;2025:;Volume ( 030 ):;issue: 010
dc.contenttypeFulltext


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