Multi-Channel EEG-based Multi-Class Emotion Recognition From Multiple Frequency Bands
Author:
Affiliation:
1. Visvesvaraya National Institute of Technology,Department of Electronics and Communication Engineering,Nagpur,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10135544/10136027/10136120.pdf?arnumber=10136120
Reference18 articles.
1. DEAP: A Database for Emotion Analysis ;Using Physiological Signals
2. Adaptive Tunable Q Wavelet Transform-Based Emotion Identification
3. Graph-Embedded Convolutional Neural Network for Image-based EEG Emotion Recognition
4. Subject-independent eeg emotion recognition with hybrid spatio-temporal gru-conv architecture;xu;Medical & Biological Engineering & Computing,2022
5. EEG Feature Extraction and Data Augmentation in Emotion Recognition
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1. Emotion Recognition Using Wavelet Synchrosqueezing Transform Integrated With Ensemble Deep Learning;IEEE Sensors Journal;2024-01-01
2. EVNCERS: An Integrated Eigenvector Centrality-Variational Nonlinear Chirp Mode Decomposition-Based EEG Rhythm Separation for Automatic Emotion Recognition;IEEE Sensors Journal;2023-09-15
3. CycleMVAE: Benchmarking End-to-End Cycle-Consistent Multi-Task Variational Autoencoder for EEG-Based Emotion Recognition;2023 IEEE Region 10 Symposium (TENSYMP);2023-09-06
4. Emotion Recognition using Machine Learning Models on Electroencephalogram (EEG) Data;2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS);2023-08-23
5. The Efficacy and Utility of Lower-Dimensional Riemannian Geometry for EEG-Based Emotion Classification;Applied Sciences;2023-07-17
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