Classification of Epileptic and Healthy Individual Eeg Signals Using Neural Networks
| dc.authorid | AYKAT, Sukru/0000-0003-1738-3696 | |
| dc.authorscopusid | 57214818735 | |
| dc.authorscopusid | 8268513100 | |
| dc.authorscopusid | 9744137200 | |
| dc.authorwosid | Ensari, Tolga/D-3799-2019 | |
| dc.authorwosid | Senan, Sibel/C-6665-2019 | |
| dc.authorwosid | AYKAT, Şükrü/IZF-0285-2023 | |
| dc.contributor.author | Aykat, Sukru | |
| dc.contributor.author | Senan, Sibel | |
| dc.contributor.author | Ensari, Tolga | |
| dc.contributor.author | Aykat, Şükrü | |
| dc.contributor.other | Department of Computer Engineering / Bilgisayar Mühendisliği Bölümü | |
| dc.date.accessioned | 2025-02-15T19:35:17Z | |
| dc.date.available | 2025-02-15T19:35:17Z | |
| dc.date.issued | 2020 | |
| dc.department | Artuklu University | en_US |
| dc.department-temp | [Aykat, Sukru] Mardin Artuklu Univ, Midyat Meslek Yuksekokulu, Bilgisayar Programciligi, Mardin, Turkey; [Senan, Sibel; Ensari, Tolga] Istanbul Univ Cerrahpasa, Muhendislik Fak, Bilgisayar Muhendisligi, Istanbul, Turkey | en_US |
| dc.description | AYKAT, Sukru/0000-0003-1738-3696 | en_US |
| dc.description.abstract | Electroencephalogram (EEG) are signals used for the analysis of the electrical and functional activity of the brain. These signals are commonly used to detect epileptic seizures. The aim of this study is to classify healthy and epileptic individual EEG signals using artificial neural networks (ANN). For this purpose, the open data source of the University of Bonn was used. The success rates of the classification results obtained with the designed ANN model show the effectiveness of this ANN structure in the application under consideration. | en_US |
| dc.description.woscitationindex | Conference Proceedings Citation Index - Science | |
| dc.identifier.citationcount | 0 | |
| dc.identifier.doi | 10.1109/ubmk50275.2020.9219474 | |
| dc.identifier.endpage | 51 | en_US |
| dc.identifier.isbn | 9781728175652 | |
| dc.identifier.scopus | 2-s2.0-85095709922 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.startpage | 47 | en_US |
| dc.identifier.uri | https://doi.org/10.1109/ubmk50275.2020.9219474 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12514/6009 | |
| dc.identifier.wos | WOS:000629055500009 | |
| dc.identifier.wosquality | N/A | |
| dc.language.iso | tr | en_US |
| dc.publisher | Ieee | en_US |
| dc.relation.ispartof | 5th International Conference on Computer Science and Engineering (UBMK) -- SEP 09-11, 2020 -- Diyarbakir, TURKEY | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.scopus.citedbyCount | 0 | |
| dc.subject | Eeg Signal | en_US |
| dc.subject | Artificial Neural Networks | en_US |
| dc.subject | Wavelet Transform | en_US |
| dc.title | Classification of Epileptic and Healthy Individual Eeg Signals Using Neural Networks | en_US |
| dc.type | Conference Object | en_US |
| dc.wos.citedbyCount | 0 | |
| dspace.entity.type | Publication | |
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