Show simple item record

contributor authorRostami, Ghodsiyeh
contributor authorChen, Po-Han
contributor authorHosseini, Mahdi S.
date accessioned2026-08-20T21:27:23Z
date available2026-08-20T21:27:23Z
date copyright2026/02/06
date issued2026
identifier otherJCCEE5.CPENG-7090.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314482
description abstractAbstractImage-based crack detection algorithms are increasingly in demand in infrastructure monitoring, as early detection of cracks is of paramount importance for timely maintenance planning. While deep learning has significantly advanced crack detection ...Practical ApplicationsInspecting infrastructure such as bridges, roads, and buildings is critical to ensure safety, however, traditional methods are often slow, expensive, and pose safety risks for workers. As a result, there has been a shift toward using ...
publisherAmerican Society of Civil Engineers
titleSegment Any Crack: Deep Semantic Segmentation Adaptation for Crack Detection
typeJournal Article
journal volume40
journal issue3
journal titleJournal of Computing in Civil Engineering
identifier doi10.1061/JCCEE5.CPENG-7090
journal fristpage04026020-1
journal lastpage04026020-14
page14
treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 003
contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record