Elektroensefalografi Verilerinin Yarı-güdümlü Öğrenme ile Otomatik Olarak İşaretlenmesi

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dc.contributor.author Köktürk, Başak Esin
dc.contributor.author Karaçalı, Bilge
dc.contributor.author Karaçalı, Bilge
dc.contributor.other 03.05. Department of Electrical and Electronics Engineering
dc.contributor.other 03. Faculty of Engineering
dc.contributor.other 01. Izmir Institute of Technology
dc.coverage.doi 10.1109/SIU.2012.6204600
dc.date.accessioned 2021-01-24T18:28:52Z
dc.date.available 2021-01-24T18:28:52Z
dc.date.issued 2012
dc.description.abstract In 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.identifier.doi 10.1109/SIU.2012.6204600 en_US
dc.identifier.isbn 978-146730056-8
dc.identifier.scopus 2-s2.0-84863455167
dc.identifier.uri https://doi.org/10.1109/SIU.2012.6204600
dc.identifier.uri https://hdl.handle.net/11147/9869
dc.language.iso tr en_US
dc.publisher IEEE en_US
dc.relation.ispartof 2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedings en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Electroencephalogram en_US
dc.subject Independent component analysis en_US
dc.subject Quasi-supervised learning en_US
dc.subject Wavelet transform en_US
dc.title Elektroensefalografi Verilerinin Yarı-güdümlü Öğrenme ile Otomatik Olarak İşaretlenmesi en_US
dc.title.alternative Automated Labeling of Electroencephalography Data Using Quasi-Supervised Learning en_US
dc.type Conference Object en_US
dspace.entity.type Publication
gdc.author.institutional Köktürk, Başak Esin
gdc.author.institutional Karaçalı, Bilge
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gdc.coar.access open access
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gdc.description.department İzmir Institute of Technology. Electrical and Electronics Engineering en_US
gdc.description.endpage 4
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.startpage 1
gdc.description.wosquality N/A
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gdc.oaire.sciencefields 03 medical and health sciences
gdc.oaire.sciencefields 0302 clinical medicine
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