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dc.contributor.authorChelli, Ali
dc.contributor.authorPätzold, Matthias Uwe
dc.date.accessioned2020-03-25T00:36:12Z
dc.date.available2020-03-25T00:36:12Z
dc.date.created2019-11-12T12:27:27Z
dc.date.issued2019
dc.identifier.citationChelli, A. & Pätzold, M. U. (2019). Fall Detection Based on the Instantaneous Doppler Frequency: A Machine Learning Approach. In IEEE Wireless Communications and Networking Conference : Proceedings. USA: IEEE. doi:en_US
dc.identifier.isbn978-1-5386-7646-2
dc.identifier.issn1558-2612
dc.identifier.urihttps://hdl.handle.net/11250/2648455
dc.descriptionAuthor's accepted manuscript (postprint).en_US
dc.description© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.descriptionAvailable from 19/04/2021.
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.ispartof2019 IEEE Wireless Communications and Networking Conference (WCNC)
dc.titleFall Detection Based on the Instantaneous Doppler Frequency : A Machine Learning Approachen_US
dc.typeChapteren_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© 2019 IEEEen_US
dc.subject.nsiVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420en_US
dc.subject.nsiVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550en_US
dc.source.pagenumber7en_US
dc.source.journalIEEE Wireless Communications and Networking Conference : Proceedingsen_US
dc.identifier.doi10.1109/WCNC.2019.8885692
dc.identifier.cristin1746463
dc.relation.projectNorges forskningsråd: 261895en_US
cristin.qualitycode1


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