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dc.contributor.authorYurtman, Arasen_US
dc.contributor.authorBarshan, Barshanen_US
dc.coverage.spatialFethiye, Turkeyen_US
dc.date.accessioned2016-02-08T12:14:16Z
dc.date.available2016-02-08T12:14:16Z
dc.date.issued2012-04en_US
dc.identifier.urihttp://hdl.handle.net/11693/28211
dc.descriptionConference Name: 20th IEEE Conference on Signal Processing and Communications Applications, 2012
dc.descriptionDate of Conference: 18-20 April 2012
dc.description.abstractThis paper provides a comparative study on the different techniques of classifying human activities using a tag-based radio-frequency (RF) localization system. Non-uniformly-sampled data containing position measurements of the tags on the body is first converted to a uniformly-sampled one using different curve-fitting algorithms. Then, the data is partitioned into segments. Finally, various classification techniques are applied to classify human activities. Curve-fitting, segmentation, and classification methods are compared using different cross-validation techniques and the combination resulting in the best performance is presented. The results indicate that the system demonstrates acceptable performance despite the fact that tag-based RF localization is not very accurate.en_US
dc.language.isoTurkishen_US
dc.source.titleProceedings of the 20th IEEE Conference on Signal Processing and Communications Applications, 2012en_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/SIU.2012.6204571en_US
dc.subjectClassification methodsen_US
dc.subjectClassification techniqueen_US
dc.subjectComparative studiesen_US
dc.subjectCross-validation techniqueen_US
dc.subjectHuman activitiesen_US
dc.subjectHuman activity recognitionen_US
dc.subjectLocalization systemen_US
dc.subjectRadio frequenciesen_US
dc.subjectTag-baseden_US
dc.subjectSignal processingen_US
dc.subjectCurve fittingen_US
dc.titleHuman activity recognition using tag-based localizationen_US
dc.title.alternativeEtiket-tabanlı konumlama ile insan aktivitelerinin tanınmasıen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.identifier.doi10.1109/SIU.2012.6204571en_US
dc.publisherIEEE


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