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Condition Evaluation of Mud Spots in Railroad Ballast Using Deep Learning

dc.contributor.authorDing, Kelin
dc.contributor.authorQamhia, Issam I. A.
dc.contributor.authorHart, John M.
dc.contributor.authorTutumluer, Erol
dc.date.accessioned2026-08-20T11:11:21Z
dc.date.available2026-08-20T11:11:21Z
dc.date.copyright2025/08/19
dc.date.issued2025
dc.identifier.otherJITSE4.ISENG-2700.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311817
dc.description.abstractAbstractRailroad ballast fouling and degradation can lead to poor drainage, settlement, and reduced lateral stability. Reliable ballast condition evaluation during track inspections can help detect and eliminate such issues, which is essential to track ...
dc.publisherAmerican Society of Civil Engineers
dc.titleCondition Evaluation of Mud Spots in Railroad Ballast Using Deep Learning
dc.typeJournal Article
dc.journal.volume31
dc.journal.issue4
dc.journal.titleJournal of Infrastructure Systems
dc.identifier.doi10.1061/JITSE4.ISENG-2700
dc.journal.fristpage04025028-1
dc.journal.lastpage04025028-12
dc.page12
dc.treeJournal of Infrastructure Systems:;2025:;Volume ( 031 ):;issue: 004
dc.contenttypeFulltext


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