Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/3617
Title: Estimation of Emotion Status Using IAPS Image Data Set
Other Titles: IAPS Goruntu Veri Seti Kullanarak Duygu Durum Kestirimi
Authors: Yesilkaya B.
Guren O.
Bahar M.T.
Turhal L.N.
Akan A.
Keywords: EGE
Emotion
Emotion Recognition
Ensemble Classifier
Feature Vector
International Affective Image System
K-nearest neighbour
Support vector machines
Nearest neighbor search
Speech recognition
Support vector machines
Classification methods
Effective analysis
Emotion analysis
Emotion modelling
Emotion recognition
Feature vectors
Human Machine Interface
K-nearest neighbours
Signal processing
Publisher: Institute of Electrical and Electronics Engineers Inc.
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.
Description: 28th Signal Processing and Communications Applications Conference, SIU 2020 -- 5 October 2020 through 7 October 2020 -- 166413
URI: https://doi.org/10.1109/SIU49456.2020.9302223
https://hdl.handle.net/20.500.14365/3617
ISBN: 9.78173E+12
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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