An emotion recognition embedded system using a lightweight deep learning model

An emotion recognition embedded system using a lightweight deep learning model

Background: Diagnosing emotional states would improve human-computer interaction (HCI) systems to be more effective in practice. Correlations between Electroencephalography (EEG) signals and emotions have been shown in various research; therefore, EEG signal-based methods are the most accurate and i...

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Bibliographic Details
Main Authors: Mehdi Bazargani, Amir Tahmasebi, Mohammadreza Yazdchi, Zahra Baharlouei
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2023-01-01
Series:Journal of Medical Signals and Sensors
Subjects:
convolutional neural network
electroencephalography
embedded system
emotion recognition
Online Access:http://www.jmssjournal.net/article.asp?issn=2228-7477;year=2023;volume=13;issue=4;spage=272;epage=279;aulast=Bazargani

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http://www.jmssjournal.net/article.asp?issn=2228-7477;year=2023;volume=13;issue=4;spage=272;epage=279;aulast=Bazargani

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