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dc.contributor.authorFarley, Steff
dc.contributor.authorHunsicker, Eugenie
dc.contributor.otherHodgkinson, Jo
dc.contributor.otherGordon, Oliver
dc.contributor.otherTurner, Joanna
dc.contributor.otherSoltoggio, Andrea
dc.contributor.otherMoriarty, Philip
dc.date.accessioned2020-09-01T07:54:28Z
dc.date.available2020-09-01T07:54:28Z
dc.date.issued2020-09-01
dc.identifier.urihttps://rdmc.nottingham.ac.uk/handle/internal/8606
dc.description.abstractTraining/Testing images and trained UNet model for the paper "Improving the Segmentation of Scanning Probe Microscope Images using Convolutional Neural Networks", Farley et al.en_UK
dc.language.isoenen_UK
dc.publisherThe University of Nottinghamen_UK
dc.rightsCC-BY*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subject.lcshScanning probe microscopyen_UK
dc.subject.lcshImage segmentationen_UK
dc.subject.lcshNeural networks (Computer science)en_UK
dc.subject.lcshMachine learningen_UK
dc.titleImproving the segmentation of scanning probe microscope images using convolutional neural networksen_UK
dc.identifier.doihttp://doi.org/10.17639/nott.7072
dc.subject.freeAFM, Machine Learning, Neural Networks, CNN, Image Processingen_UK
dc.subject.jacsComputer Sciences::Artificial intelligence::Machine learning, Automated reasoningen_UK
dc.subject.lcQ Science::QH Natural history. Biology::QH201 Microscopyen_UK
uon.divisionUniversity of Nottingham, UK Campusen_UK
uon.divisionOtheren_UK
uon.funder.controlledOtheren_UK
uon.funder.controlledEngineering & Physical Sciences Research Councilen_UK
uon.datatypeCNN training data and trained networken_UK
uon.funder.freeUniversity of Loughboroughen_UK
uon.grantEP/N02379X/1en_UK
uon.collectionmethodAsylum Research MFP-3D AFMen_UK
uon.institutes-centresUniversity of Nottingham, UK Campusen_UK
uon.preservation.rarelyaccessedtrue


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