Vis enkel innførsel

dc.contributor.authorMuaaz, Muhammad
dc.contributor.authorChelli, Ali
dc.contributor.authorPätzold, Matthias Uwe
dc.date.accessioned2021-03-24T14:32:36Z
dc.date.available2021-03-24T14:32:36Z
dc.date.created2020-07-16T16:14:44Z
dc.date.issued2020
dc.identifier.citationMuaaz, M., Chelli, A. & Pätzold, M. U. (2020). WiHAR : From Wi-Fi Channel State Information to Unobtrusive Human Activity Recognition. IEEE Vehicular Technology Conference, 19732447.en_US
dc.identifier.isbn978-1-7281-5207-3
dc.identifier.issn2577-2465
dc.identifier.urihttps://hdl.handle.net/11250/2735336
dc.descriptionAuthor's accepted manuscript.en_US
dc.description© 2020 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.language.isoengen_US
dc.publisherIEEEen_US
dc.titleWiHAR : From Wi-Fi Channel State Information to Unobtrusive Human Activity Recognitionen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© 2020 IEEEen_US
dc.subject.nsiVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550en_US
dc.source.pagenumber7en_US
dc.source.journalIEEE Vehicular Technology Conferenceen_US
dc.identifier.doihttps://doi.org/10.1109/VTC2020-Spring48590.2020.9128418
dc.identifier.cristin1819632
dc.relation.projectNorges forskningsråd: 261895en_US
dc.source.articlenumber19732447en_US
cristin.qualitycode1


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel