Importance Ranking of Features for Human Micro-Doppler Classification with a Radar Network

Basit Öğe Kaydı
dc.authoridGurbuz, Ali Cafer/0000-0001-8923-0299|Gurbuz, Sevgi Zubeyde/0000-0001-7487-9087|Yuksel, Melda/0000-0002-8029-631X;
dc.contributor.authorGurbuz, Sevgi Zubeyde
dc.contributor.authorTekeli, Burkan
dc.contributor.authorYuksel, Melda
dc.contributor.authorKarabacak, Cesur
dc.contributor.authorGurbuz, Ali Cafer
dc.contributor.authorGuldogan, Mehmet Burak
dc.date.accessioned2025-10-24T18:10:29Z
dc.date.available2025-10-24T18:10:29Z
dc.date.issued2013
dc.departmentMalatya Turgut Özal Üniversitesi
dc.description16th International Conference on Information Fusion (FUSION) -- JUL 09-12, 2013 -- Istanbul, TURKEY
dc.description.abstractOver the past decade, the human micro-Doppler signature has been a subject of intense research. In particular, much work has been done in relation to computing features for use in a variety of classification problems, such as arm swing detection, activity classification, and target identification. Although dozens of features have been proposed for these purposes, little work has examined the issue of which features are more important - i.e., have a greater impact on classification performance - than others. In this work, an information theoretic approach is applied to compute the importance ranking of features prior to classification for the specific problem of discriminating human walking from running. Results show that the ranking of features according to mutual information directly relates to classification performance using support vector machines.
dc.description.sponsorshipEU [PIRG-GA-2010-268276]
dc.description.sponsorshipThis work was supported in part by EU FP7 Project No. PIRG-GA-2010-268276 (COGSENSE).
dc.description.sponsorshipHAVELSAN,METEKSAN SAVUNMA,TUBITAK,METRON Sci Solut,Off Naval Res Global Sci & Technol,Ankara Univ,Sabanci Univ,STM,TAI,ASELSAN,Koc Bilgi Savunma Teknolojileri A S,Kale Havacilik,Int Soc Infromat Fus,IEEE,AESS
dc.identifier.endpage616
dc.identifier.isbn978-605-86311-1-3
dc.identifier.issn#DEĞER!
dc.identifier.scopus2-s2.0-84890824413
dc.identifier.scopusqualityN/A
dc.identifier.startpage610
dc.identifier.urihttps://hdl.handle.net/20.500.12899/4197
dc.identifier.wosWOS:000341370000081
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIeee
dc.relation.ispartof2013 16th International Conference On Information Fusion (Fusion)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20251023
dc.subjecthuman micro-Doppler; feature selection; classification; multistatic radar; radar network
dc.titleImportance Ranking of Features for Human Micro-Doppler Classification with a Radar Network
dc.typeConference Object

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu