Feature detection in guided wave ultrasound measurements using simulated spectrograms and generative machine learning

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dc.article.end-page15en
dc.article.start-page1en
dc.citation.doi10.1016/J.NDTEINT.2024.103036en
dc.contributor.authorIsaac Setshedien
dc.contributor.authorD Wilkeen
dc.contributor.authorPhilip Lovedayen
dc.date.accessioned2024-10-28T13:34:21Z
dc.date.available2024-10-28T13:34:21Z
dc.facultyFACULTY OF ENGINEERING & THE BUILT ENVIRONMENTen
dc.identifier.citationWOSen
dc.identifier.issn0963-8695en
dc.identifier.urihttps://hdl.handle.net/10539/42036
dc.journal.titleFeature detection in guided wave ultrasound measurements using simulated spectrograms and generative machine learningen
dc.journal.volume143en
dc.school3.06en
dc.titleFeature detection in guided wave ultrasound measurements using simulated spectrograms and generative machine learningen
dc.typeJournal Articleen
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