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dc.contributor.authorGordon, Oliver
dc.contributor.authorMoriarty, Philip
dc.contributor.otherEugenie, Hunsicker
dc.contributor.otherFarley, Steff
dc.contributor.otherHodgkinson, Jo EA
dc.coverage.temporal2005-2007en_UK
dc.date.accessioned2020-08-05T13:32:57Z
dc.date.available2020-08-05T13:32:57Z
dc.date.issued2020-08-05
dc.identifier.urihttps://rdmc.nottingham.ac.uk/handle/internal/8601
dc.description.abstractA dataset of >5000 variable AFM dewetting images as classified by a machine learning system. This network was trained on specific, automatically labelled simulations of target nanoparticle structures present within the dataset.en_UK
dc.language.isoenen_UK
dc.publisherThe University of Nottinghamen_UK
dc.relation.urihttps://github.com/OGordon100/pyRabanien_UK
dc.rightsCC-BY*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subject.lcshMachine learningen_UK
dc.subject.lcshData miningen_UK
dc.subject.lcshNanoscienceen_UK
dc.subject.lcshAtomic force microscopyen_UK
dc.subject.lcshNanoparticlesen_UK
dc.titleAutomated Searching and Identification of Self-Organised Nanostructures - Output Imagesen_UK
dc.typedataset
dc.identifier.doihttp://doi.org/10.17639/nott.7067
dc.subject.freemachine learning, datamining, nanoscience, atomic force microscopy, dewetting, nanoparticleen_UK
dc.subject.jacsPhysical sciencesen_UK
dc.subject.lcQ Scienceen_UK
dc.subject.lcT Technologyen_UK
dc.date.collection2020en_UK
uon.divisionUniversity of Nottingham, UK Campus::Faculty of Science::School of Physics and Astronomyen_UK
uon.funder.controlledEngineering & Physical Sciences Research Councilen_UK
uon.datatypeimages & metadata csven_UK
uon.grantEP/N02379X/1en_UK
uon.collectionmethodImages collected by Asylum Research MFP-3D, processing through custom python codeen_UK
uon.preservation.rarelyaccessedtrue


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