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dc.contributor.authorAgrawal, Deepika Vikas
dc.contributor.authorGupta, Varun
dc.contributor.authorRama Krishna, C.
dc.date.accessioned2026-08-20T12:01:24Z
dc.date.available2026-08-20T12:01:24Z
dc.date.copyright2026/04/06
dc.date.issued2026
dc.identifier.otherJPEODX.PVENG-1768.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4312986
dc.description.abstractAbstractPotholes pose a significant challenge to road safety, affecting daily life and economic activities. Prompt and effective pothole management is crucial for mitigating their adverse effects. Machine-learning (ML) methods help in automatic pothole ...Practical ApplicationsPotholes damage roads and can lead to traffic accidents, especially in poorly lit or weather-affected regions in which visual inspections are unreliable. This study presents a self-supervised learning–based approach for detecting ...
dc.publisherAmerican Society of Civil Engineers
dc.titleEnhancing Pothole Detection with Self-Supervised Learning: A Hybrid Contrastive and Noncontrastive Approach for Label-Efficient Segmentation
dc.typeJournal Article
dc.journal.volume152
dc.journal.issue2
dc.journal.titleJournal of Transportation Engineering, Part B: Pavements
dc.identifier.doi10.1061/JPEODX.PVENG-1768
dc.journal.fristpage04026019-1
dc.journal.lastpage04026019-19
dc.page19
dc.treeJournal of Transportation Engineering, Part B: Pavements:;2026:;Volume ( 152 ):;issue: 002
dc.contenttypeFulltext


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