Estimation of Emotion Status Using Iaps Image Data Set
| dc.contributor.author | Yesilkaya B. | |
| dc.contributor.author | Guren O. | |
| dc.contributor.author | Bahar M.T. | |
| dc.contributor.author | Turhal L.N. | |
| dc.contributor.author | Akan A. | |
| dc.date.accessioned | 2023-06-16T15:01:48Z | |
| dc.date.available | 2023-06-16T15:01:48Z | |
| dc.date.issued | 2020 | |
| dc.description | 28th Signal Processing and Communications Applications Conference, SIU 2020 -- 5 October 2020 through 7 October 2020 -- 166413 | en_US |
| dc.description.abstract | Emotion recognition is an effective analysis method used to increase the interaction between human-machine interface. EEG based emotion recognition studies based on brain signals are preferred in order to provide healthy results of emotion analysis experiments. In this study, emotion recognition analysis was performed in accordance with dimensional emotion modelling. Data cleaning was performed by applying the necessary filters on the recorded data. The feature vector was then created and the success rate was determined using support vector machines and classification methods such as K-nearest neighbour. © 2020 IEEE. | en_US |
| dc.identifier.doi | 10.1109/SIU49456.2020.9302223 | |
| dc.identifier.isbn | 9.78E+12 | |
| dc.identifier.scopus | 2-s2.0-85100311182 | |
| dc.identifier.uri | https://doi.org/10.1109/SIU49456.2020.9302223 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14365/3617 | |
| dc.language.iso | tr | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.relation.ispartof | 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | EGE | en_US |
| dc.subject | Emotion | en_US |
| dc.subject | Emotion Recognition | en_US |
| dc.subject | Ensemble Classifier | en_US |
| dc.subject | Feature Vector | en_US |
| dc.subject | International Affective Image System | en_US |
| dc.subject | K-nearest neighbour | en_US |
| dc.subject | Support vector machines | en_US |
| dc.subject | Nearest neighbor search | en_US |
| dc.subject | Speech recognition | en_US |
| dc.subject | Support vector machines | en_US |
| dc.subject | Classification methods | en_US |
| dc.subject | Effective analysis | en_US |
| dc.subject | Emotion analysis | en_US |
| dc.subject | Emotion modelling | en_US |
| dc.subject | Emotion recognition | en_US |
| dc.subject | Feature vectors | en_US |
| dc.subject | Human Machine Interface | en_US |
| dc.subject | K-nearest neighbours | en_US |
| dc.subject | Signal processing | en_US |
| dc.title | Estimation of Emotion Status Using Iaps Image Data Set | en_US |
| dc.title.alternative | Iaps Goruntu Veri Seti Kullanarak Duygu Durum Kestirimi | en_US |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
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| gdc.description.departmenttemp | Yesilkaya, B., Izmir Kâtip Çelebi Üniversitesi, Biyomedikal Mühendisli?i Bölümü, Izmir, Turkey; Guren, O., Izmir Kâtip Çelebi Üniversitesi, Biyomedikal Mühendisli?i Bölümü, Izmir, Turkey; Bahar, M.T., Izmir Kâtip Çelebi Üniversitesi, Biyomedikal Mühendisli?i Bölümü, Izmir, Turkey; Turhal, L.N., Izmir Kâtip Çelebi Üniversitesi, Biyomedikal Mühendisli?i Bölümü, Izmir, Turkey; Akan, A., Izmir Ekonomi Üniversitesi, Elektrik Elektronik Mühendisli?i Bölümü, Izmir, Turkey | 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 | |
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| gdc.identifier.openalex | W3120213766 | |
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| gdc.virtual.author | Akan, Aydın | |
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