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Exploring Segment Anything Foundation Models for Out of Domain Crevasse Drone Image Segmentation

dc.contributor.authorWallace, Steven
dc.contributor.authorDurrant, Aiden
dc.contributor.authorHarcourt, William
dc.contributor.authorHann, Richard
dc.contributor.authorLeontidis, Georgios
dc.contributor.editorLutchyn, Tetiana
dc.contributor.editorRivera, Adín Ramírez
dc.contributor.editorRicaud, Benjamin
dc.contributor.institutionUniversity of Aberdeen.Natural & Computing Sciencesen
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.contributor.institutionUniversity of Aberdeen.Geography & Environmenten
dc.contributor.institutionUniversity of Aberdeen.Vice Principalsen
dc.date.accessioned2024-11-18T19:05:01Z
dc.date.available2024-11-18T19:05:01Z
dc.date.issued2025-01
dc.format.extent14
dc.format.extent8755688
dc.identifier298689189
dc.identifier39cb889f-c289-4b3a-8416-a979b2f27af2
dc.identifier85219135647
dc.identifier85219135647
dc.identifier.citationWallace, S, Durrant, A, Harcourt, W, Hann, R & Leontidis, G 2025, Exploring Segment Anything Foundation Models for Out of Domain Crevasse Drone Image Segmentation. in T Lutchyn, A R Rivera & B Ricaud (eds), Proceedings of the 6th Northern Lights Deep Learning Conference (NLDL). vol. 265, Proceedings of Machine Learning Research, vol. 265, MLR Press, pp. 255-268, 6th Northern Lights Deep Learning Conference, Tromsø, Norway, 7/01/25. < https://proceedings.mlr.press/v265/wallace25a.html >en
dc.identifier.citationconferenceen
dc.identifier.issn2640-3498
dc.identifier.otherORCID: /0000-0003-3897-3193/work/171978771
dc.identifier.otherORCID: /0000-0002-8375-4523/work/171978877
dc.identifier.otherORCID: /0000-0001-6671-5568/work/171979840
dc.identifier.urihttps://hdl.handle.net/2164/24639
dc.identifier.urlhttps://www.nldl.org/en
dc.identifier.urlhttps://proceedings.mlr.press/v265/wallace25a.htmlen
dc.identifier.vol265en
dc.language.isoeng
dc.publisherMLR Press
dc.relation.ispartofProceedings of the 6th Northern Lights Deep Learning Conference (NLDL)en
dc.relation.ispartofseriesProceedings of Machine Learning Researchen
dc.subject2040 Data and Artificial Intelligenceen
dc.subjectDeep Learningen
dc.subjectFoundation Modelsen
dc.subjectImage Segmentationen
dc.subjectClimate Scienceen
dc.subjectRemote Sensingen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectQE Geologyen
dc.subjectSupplementary Informationen
dc.subject.lccQA75en
dc.subject.lccQEen
dc.titleExploring Segment Anything Foundation Models for Out of Domain Crevasse Drone Image Segmentationen
dc.typeConference itemen

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