Emotion Recognition Method Based on EEG Signals: 4D-CapsBLnet Model Integrating Spatio-Temporal Features-Reference-Cited by-同舟云学术

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Emotion Recognition Method Based on EEG Signals: 4D-CapsBLnet Model Integrating Spatio-Temporal Features

Published:2024-04-26 Issue: Volume:30 Page:82-87
ISSN:
Container-title:2024 IEEE 2nd International Conference on Control, Electronics and Computer Technology (ICCECT)
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Author:

Zhuang Chenze¹,Dai Licao²,Fu Qiang³

Affiliation:

1. College of Computer Science, University of South China,Hengyang,China,421001

2. Human Factor Institute, University of South China,Hengyang,China,421001

3. University of South China,Department of Management Science and Engineering,Hengyang,China,421001

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10545644/10545608/10545975.pdf?arnumber=10545975

Reference13 articles.

1. Classification of EEG signals using neural network and logistic regression

2. From Regional to Global Brain: A Novel Hierarchical Spatial-Temporal Neural Network Model for EEG Emotion Recognition;Yang;IEEE Transactions on Affective Computing,2019

3. Core-Brain-Network-Based Multilayer Convolutional Neural Network for Emotion Recognition

4. Investigating Critical Frequency Bands and Channels for EEG-Based Emotion Recognition with Deep Neural Networks

5. EmotioNet: A 3-D Convolutional Neural Network for EEG-based Emotion Recognition

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