Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/9869
Full metadata record
DC FieldValueLanguage
dc.contributor.authorKöktürk, Başak Esin-
dc.contributor.authorKaraçalı, Bilge-
dc.date.accessioned2021-01-24T18:28:52Z-
dc.date.available2021-01-24T18:28:52Z-
dc.date.issued2012-
dc.identifier.isbn978-146730056-8-
dc.identifier.urihttps://doi.org/10.1109/SIU.2012.6204600-
dc.identifier.urihttps://hdl.handle.net/11147/9869-
dc.description.abstractIn this study, the separation of the stimulus effects from the baseline was investigated in electroencephalography data recorded under different visual stimuli using quasi-supervised learning. The data feature vectors were constructed using independent component analysis and wavelet transform, and then, these feature vectors were separated using quasi-supervised learning. Experiment results showed that the EEG data of the stimuli can be separated using quasi-supervised learning. © 2012 IEEE.en_US
dc.language.isotren_US
dc.publisherIEEEen_US
dc.relation.ispartof2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedingsen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectElectroencephalogramen_US
dc.subjectIndependent component analysisen_US
dc.subjectQuasi-supervised learningen_US
dc.subjectWavelet transformen_US
dc.titleElektroensefalografi verilerinin yarı-güdümlü öğrenme ile otomatik olarak işaretlenmesien_US
dc.title.alternativeAutomated labeling of electroencephalography data using quasi-supervised learningen_US
dc.typeConference Objecten_US
dc.institutionauthorKöktürk, Başak Esin-
dc.institutionauthorKaraçalı, Bilge-
dc.departmentİzmir Institute of Technology. Electrical and Electronics Engineeringen_US
dc.identifier.scopus2-s2.0-84863455167en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1109/SIU.2012.6204600-
dc.relation.doi10.1109/SIU.2012.6204600en_US
dc.coverage.doi10.1109/SIU.2012.6204600en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.languageiso639-1tr-
item.grantfulltextnone-
item.openairetypeConference Object-
crisitem.author.dept03.05. Department of Electrical and Electronics Engineering-
Appears in Collections:Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

1
checked on Apr 5, 2024

Page view(s)

120
checked on Apr 15, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.