Liking Prediction Using fNIRS and Machine Learning: Comparison of Feature Extraction Methods

dc.authorscopusid57904980500
dc.authorscopusid56329345400
dc.authorscopusid57904169000
dc.authorscopusid57190280446
dc.contributor.authorKoksal, M.Y.
dc.contributor.authorCakar, T.
dc.contributor.authorTuna, E.
dc.contributor.authorGirisken, Y.
dc.date.accessioned2024-07-18T20:17:11Z
dc.date.available2024-07-18T20:17:11Z
dc.date.issued2022
dc.description30th Signal Processing and Communications Applications Conference, SIU 2022 -- 15 May 2022 through 18 May 2022 -- -- 182415en_US
dc.description.abstractThe fMRI method, which is generally used to detect behavioral patterns, draws attention with its expensive and impractical features. On the other hand, near infrared spectroscopy (fNIRS) method is less expensive and portable, but it is as effective as fMRI in creating a good prediction model. With this method, a model has been developed that can predict whether people like a stimulus or not, using machine learning various algorithms. A comparison was made between feature extraction methods, which was the main focus while developing the model. © 2022 IEEE.en_US
dc.identifier.doi10.1109/SIU55565.2022.9864887
dc.identifier.isbn9781665450928
dc.identifier.scopus2-s2.0-85138706426en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/SIU55565.2022.9864887
dc.identifier.urihttps://hdl.handle.net/11411/6434
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2022 30th Signal Processing and Communications Applications Conference, SIU 2022en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDecision-Makingen_US
dc.subjectFeature Extractionen_US
dc.subjectFnırsen_US
dc.subjectMachine Learningen_US
dc.subjectOptical Brain İmagingen_US
dc.subjectBehavioral Researchen_US
dc.subjectBrain Mappingen_US
dc.subjectExtractionen_US
dc.subjectFeature Extractionen_US
dc.subjectInfrared Devicesen_US
dc.subjectLearning Systemsen_US
dc.subjectNear İnfrared Spectroscopyen_US
dc.subjectBehavioral Patternsen_US
dc.subjectDecisions Makingsen_US
dc.subjectFeature Extraction Methodsen_US
dc.subjectFeatures Extractionen_US
dc.subjectFnırsen_US
dc.subjectMachine-Learningen_US
dc.subjectOptical Brain İmagingen_US
dc.subjectPrediction Modellingen_US
dc.subjectDecision Makingen_US
dc.titleLiking Prediction Using fNIRS and Machine Learning: Comparison of Feature Extraction Methodsen_US
dc.title.alternativefNIRS ve Makine Ö?renmesi ile Be?eni Tahmini: Öznitelik Indirgeme Yöntemlerinin Karşilaştirilmasien_US
dc.typeConference Objecten_US

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