Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/5614
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dc.contributor.authorSen, Sena Yagmur-
dc.contributor.authorAkan, Aydin-
dc.contributor.authorCura, Ozlem Karabiber-
dc.date.accessioned2024-11-25T16:53:56Z-
dc.date.available2024-11-25T16:53:56Z-
dc.date.issued2024-
dc.identifier.isbn9789464593617-
dc.identifier.isbn9798331519773-
dc.identifier.issn2076-1465-
dc.identifier.urihttps://doi.org/10.23919/EUSIPCO63174.2024.10715005-
dc.description.abstractThis paper presents a novel early-stage Alzheimer's dementia (AD) disease detection based on convolutional neural networks (CNNs). As it is widely used in detection and classification of AD disease, a time-frequency (TF) method has been proposed for AD detection. It has been described to address the problem of detecting early-stage AD by combining TF and CNN methods. The method is developed by utilizing the well-known structural similarity index measure (SSIM) to obtain discriminative features in each TF image. Experimental results demonstrate that the proposed method outperforms the early-stage AD detection using advanced signal decomposition algorithm that is intrinsic time-scale decomposition (ITD), and it achieves a notable improvement in terms of the detection success rates compared to AD detection from TF images of raw EEG signals.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof32nd European Signal Processing Conference (EUSIPCO) -- AUG 26-30, 2024 -- Lyon, FRANCEen_US
dc.relation.ispartofseriesEuropean Signal Processing Conference-
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAlzheimer'S Dementia (Ad)en_US
dc.subjectElectroencephalography (Eeg)en_US
dc.subjectIntrinsic Time-Scale Decomposition (Itd)en_US
dc.subjectShort-Time Fourier Transform (Stft)en_US
dc.subjectConvolutional Neural Network (Cnn)en_US
dc.titleAlzheimer's Dementia Detection: an Optimized Approach Using Itd of Eeg Signalsen_US
dc.typeConference Objecten_US
dc.identifier.doi10.23919/EUSIPCO63174.2024.10715005-
dc.identifier.scopus2-s2.0-85208442090-
dc.departmentİzmir Ekonomi Üniversitesien_US
dc.authorwosidSen, Sena Yagmur/Iup-8865-2023-
dc.authorscopusid57215314563-
dc.authorscopusid35617283100-
dc.authorscopusid57195223021-
dc.identifier.startpage1377en_US
dc.identifier.endpage1381en_US
dc.identifier.wosWOS:001349787000276-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityN/A-
dc.identifier.wosqualityN/A-
dc.description.woscitationindexConference Proceedings Citation Index - Science-
item.openairetypeConference Object-
item.grantfulltextreserved-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
crisitem.author.dept05.06. Electrical and Electronics Engineering-
crisitem.author.dept05.06. Electrical and Electronics Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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