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dc.contributor.authorAi, Changfa
dc.contributor.authorHe, Anzheng
dc.contributor.authorWu, Di
dc.contributor.authorZhang, Allen A.
dc.contributor.authorChen, Zhenyu
dc.contributor.authorSun, Yangyong
dc.contributor.authorPeng, Yi
dc.contributor.authorCheng, Huixuan
dc.date.accessioned2026-08-20T21:28:32Z
dc.date.available2026-08-20T21:28:32Z
dc.date.copyright2026/03/20
dc.date.issued2026
dc.identifier.otherJCCEE5.CPENG-7381.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314516
dc.description.abstractAbstractThis paper proposes an efficient and robust model named bridge crack segmentation network (BCS-Net), tailored for high-precision segmentation of surface cracks on concrete bridges. BCS-Net adopts an encoder-decoder framework augmented by a ...Practical ApplicationsThe bridge surface crack is a primary form of structural damage in concrete bridges and a significant focus of bridge surface inspections. Accurate detection and timely repair of surface cracks prior to their deterioration are ...
dc.publisherAmerican Society of Civil Engineers
dc.titleAn Efficient and Robust Model for Precise Surface Crack Segmentation on Concrete Bridge Structures
dc.typeJournal Article
dc.journal.volume40
dc.journal.issue4
dc.journal.titleJournal of Computing in Civil Engineering
dc.identifier.doi10.1061/JCCEE5.CPENG-7381
dc.journal.fristpage04026035-1
dc.journal.lastpage04026035-15
dc.page15
dc.treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 004
dc.contenttypeFulltext


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