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dc.contributor.authorJohansen, Thomas Haugland
dc.contributor.authorSørensen, Steffen Aagaard
dc.date.accessioned2021-02-11T14:30:48Z
dc.date.available2021-02-11T14:30:48Z
dc.date.issued2020-02-06
dc.description.abstract<p>Foraminifera are single-celled marine organisms, which may have a planktic or benthic lifestyle. During their life cycle they construct shells consisting of one or more chambers, and these shells remain as fossils in marine sediments. Classifying and counting these fossils have become an important tool in e.g. oceanography and climatology. <p>Currently the process of identifying and counting microfossils is performed manually using a microscope and is very time consuming. Developing methods to automate this process is therefore considered important across a range of research fields. <p>The first steps towards developing a deep learning model that can detect and classify microscopic foraminifera are proposed. The proposed model is based on a VGG16 model that has been pretrained on the ImageNet dataset, and adapted to the foraminifera task using transfer learning. Additionally, a novel image dataset consisting of microscopic foraminifera and sediments from the Barents Sea region is introduced.en_US
dc.identifier.citationJohansen T, Sørensen SA. Towards detection and classification of microscopic foraminifera using transfer learning. Proceedings of the Northern Lights Deep Learning Workshop. 2020;1en_US
dc.identifier.cristinIDFRIDAID 1873231
dc.identifier.doi10.7557/18.5144
dc.identifier.issn2703-6928
dc.identifier.urihttps://hdl.handle.net/10037/20559
dc.language.isoengen_US
dc.publisherSeptentrio Academic Publishingen_US
dc.relation.journalProceedings of the Northern Lights Deep Learning Workshop
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2020 The Author(s)en_US
dc.subjectVDP::Mathematics and natural science: 400::Geosciences: 450::Marine geology: 466en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Geofag: 450::Marin geologi: 466en_US
dc.titleTowards detection and classification of microscopic foraminifera using transfer learningen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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