Automated Searching and Identification of Self-Organised Nanostructures - Output Images
dc.contributor.author | Gordon, Oliver | |
dc.contributor.author | Moriarty, Philip | |
dc.contributor.other | Eugenie, Hunsicker | |
dc.contributor.other | Farley, Steff | |
dc.contributor.other | Hodgkinson, Jo EA | |
dc.coverage.temporal | 2005-2007 | en_UK |
dc.date.accessioned | 2020-08-05T13:32:57Z | |
dc.date.available | 2020-08-05T13:32:57Z | |
dc.date.issued | 2020-08-05 | |
dc.identifier.uri | https://rdmc.nottingham.ac.uk/handle/internal/8601 | |
dc.description.abstract | A 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.iso | en | en_UK |
dc.publisher | The University of Nottingham | en_UK |
dc.relation.uri | https://github.com/OGordon100/pyRabani | en_UK |
dc.rights | CC-BY | * |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
dc.subject.lcsh | Machine learning | en_UK |
dc.subject.lcsh | Data mining | en_UK |
dc.subject.lcsh | Nanoscience | en_UK |
dc.subject.lcsh | Atomic force microscopy | en_UK |
dc.subject.lcsh | Nanoparticles | en_UK |
dc.title | Automated Searching and Identification of Self-Organised Nanostructures - Output Images | en_UK |
dc.type | Dataset | |
dc.identifier.doi | http://doi.org/10.17639/nott.7067 | |
dc.subject.free | machine learning, datamining, nanoscience, atomic force microscopy, dewetting, nanoparticle | en_UK |
dc.subject.jacs | Physical sciences | en_UK |
dc.subject.lc | Q Science | en_UK |
dc.subject.lc | T Technology | en_UK |
dc.date.collection | 2020 | en_UK |
uon.division | University of Nottingham, UK Campus::Faculty of Science::School of Physics and Astronomy | en_UK |
uon.funder.controlled | Engineering & Physical Sciences Research Council | en_UK |
uon.datatype | images & metadata csv | en_UK |
uon.grant | EP/N02379X/1 | en_UK |
uon.collectionmethod | Images collected by Asylum Research MFP-3D, processing through custom python code | en_UK |
uon.preservation.rarelyaccessed | true |
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