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dc.contributor.authorChelli, Ali
dc.contributor.authorPätzold, Matthias Uwe
dc.date.accessioned2020-03-27T10:00:26Z
dc.date.available2020-03-27T10:00:26Z
dc.date.created2019-10-21T14:41:41Z
dc.date.issued2019
dc.identifier.citationChelli, A. & Pätzold, M. U. (2019). A Machine Learning Approach for Fall Detection Based on the Instantaneous Doppler Frequency. IEEE Access, 7, 166173-166189. doi:en_US
dc.identifier.issn2169-3536
dc.identifier.urihttps://hdl.handle.net/11250/2649059
dc.language.isoengen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleA Machine Learning Approach for Fall Detection Based on the Instantaneous Doppler Frequencyen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2019 The Author(s)en_US
dc.subject.nsiVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550en_US
dc.source.pagenumber166173-166189en_US
dc.source.volume7en_US
dc.source.journalIEEE Accessen_US
dc.identifier.doi10.1109/ACCESS.2019.2947739
dc.identifier.cristin1739145
dc.relation.projectNorges forskningsråd: 261895en_US
cristin.qualitycode1


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal