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An experimental methodology for automated detection of surface turbulence features in tidal stream environments

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dc.contributor.authorSlingsby, James
dc.contributor.authorScott, Beth
dc.contributor.authorKregting, Louise
dc.contributor.authorMcIlvenny, Jason
dc.contributor.authorWilson, Jared
dc.contributor.authorHelleux, Fanny
dc.contributor.authorWilliamson, Benjamin J.
dc.contributor.institutionUniversity of Aberdeen.Centre for Energy Transitionen
dc.contributor.institutionUniversity of Aberdeen.Marine Alliance for Science and Technology for Scotland (MASTS)en
dc.contributor.institutionUniversity of Aberdeen.Biological Sciencesen
dc.date.accessioned2025-03-21T21:27:01Z
dc.date.available2025-03-21T21:27:01Z
dc.date.issued2024-10-01
dc.descriptionAcknowledgments We gratefully acknowledge the support of colleagues at Marine Scotland Science, the crew/scientists of the MRV Scotia 2016/2018 cruises (particularly Chief Scientists Eric Armstrong and Adrian Tait), and ERI interns: Gael Gelis and Martin Forestier.en
dc.description.statusPeer revieweden
dc.format.extent14
dc.format.extent1861353
dc.identifier293396845
dc.identifiera0c30366-3ba4-4a77-803c-a5e653dfaa91
dc.identifier39409210
dc.identifier85206434068
dc.identifier.citationSlingsby, J, Scott, B, Kregting, L, McIlvenny, J, Wilson, J, Helleux, F & Williamson, B J 2024, 'An experimental methodology for automated detection of surface turbulence features in tidal stream environments', Sensors, vol. 24, no. 19, 6170. https://doi.org/10.3390/s24196170en
dc.identifier.doi10.3390/s24196170
dc.identifier.iss19en
dc.identifier.issn1424-8220
dc.identifier.otherORCID: /0000-0001-5412-3952/work/180764433
dc.identifier.urihttps://hdl.handle.net/2164/25185
dc.identifier.vol24en
dc.language.isoeng
dc.relation.ispartofSensorsen
dc.subjectSDG 7 - Affordable and Clean Energyen
dc.subjectSDG 14 - Life Below Wateren
dc.subjectenvironmental monitoringen
dc.subjectremote sensingen
dc.subjectmarine renewablesen
dc.subjectmachine learningen
dc.subjectdeep learningen
dc.subjectQH301 Biologyen
dc.subjectGC Oceanographyen
dc.subjectSupplementary Dataen
dc.subjectDASen
dc.subject.lccQH301en
dc.subject.lccGCen
dc.titleAn experimental methodology for automated detection of surface turbulence features in tidal stream environmentsen
dc.typeJournal articleen

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