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dc.contributor.authorHu, Xuke
dc.contributor.authorDing, Lei
dc.contributor.authorShang, Jianga
dc.contributor.authorFan, Hongchao
dc.contributor.authorNovack, Tessio
dc.contributor.authorNoskov, Alexey
dc.contributor.authorZipf, Alexander
dc.date.accessioned2022-02-08T12:45:17Z
dc.date.available2022-02-08T12:45:17Z
dc.date.created2019-12-23T19:44:39Z
dc.date.issued2020
dc.identifier.citationInternational Journal of Digital Earth. 2020, .en_US
dc.identifier.issn1753-8947
dc.identifier.urihttps://hdl.handle.net/11250/2977722
dc.descriptionThis article is not available due to copyright restrictionsen_US
dc.language.isoengen_US
dc.publisherTaylor and Francisen_US
dc.titleA Data-driven Approach to Learning Salience Models of Indoor Landmarks by Using Genetic Programmingen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber28en_US
dc.source.journalInternational Journal of Digital Earthen_US
dc.identifier.doi10.1080/17538947.2019.1701109
dc.identifier.cristin1763789
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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