Show simple item record

Training Deep Learning Segmentation Models Using Super-Resolution Crack Images for Detection of Thin Concrete Cracks

dc.contributor.authorOh, Dokyoon
dc.contributor.authorJeong, Seran
dc.contributor.authorBae, Suk-Kyoung
dc.contributor.authorKim, Byunghyun
dc.contributor.authorCho, Soojin
dc.date.accessioned2026-08-20T21:22:54Z
dc.date.available2026-08-20T21:22:54Z
dc.date.copyright2025/03/31
dc.date.issued2025
dc.identifier.otherJCCEE5.CPENG-6240.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314366
dc.description.abstractAbstractCracks are the most critical damage types on concrete structures, and they are commonly assessed based on visual inspection. Recently, there have been many attempts to replace conventional inspection with computer vision-based inspection powered ...
dc.publisherAmerican Society of Civil Engineers
dc.titleTraining Deep Learning Segmentation Models Using Super-Resolution Crack Images for Detection of Thin Concrete Cracks
dc.typeJournal Article
dc.journal.volume39
dc.journal.issue4
dc.journal.titleJournal of Computing in Civil Engineering
dc.identifier.doi10.1061/JCCEE5.CPENG-6240
dc.journal.fristpage04025035-1
dc.journal.lastpage04025035-14
dc.page14
dc.treeJournal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 004
dc.contenttypeFulltext


Files in this item

Thumbnail
Name:
JCCEE5.CPENG-6240.pdf
Size:
4.085Mb
Format:
PDF
View/Open

This item appears in the following Collection(s)

Show simple item record