Emotion recognition based on EEG using generative adversarial nets and convolutional neural network
B Pan, W Zheng - computational and Mathematical Methods in …, 2021 - Wiley Online Library
Emotion recognition plays an important role in the field of human‐computer interaction
(HCI). Automatic emotion recognition based on EEG is an important topic in brain‐computer …
(HCI). Automatic emotion recognition based on EEG is an important topic in brain‐computer …
Emotion recognition using three-dimensional feature and convolutional neural network from multichannel EEG signals
H Chao, L Dong - IEEE sensors journal, 2020 - ieeexplore.ieee.org
Using electroencephalogram (EEG) signal to recognize emotional states has become a
research hotspot of affective computing. Previous emotion recognition methods almost …
research hotspot of affective computing. Previous emotion recognition methods almost …
An investigation of deep learning models for EEG-based emotion recognition
Y Zhang, J Chen, JH Tan, Y Chen, Y Chen… - Frontiers in …, 2020 - frontiersin.org
Emotion is the human brain reacting to objective things. In real life, human emotions are
complex and changeable, so research into emotion recognition is of great significance in …
complex and changeable, so research into emotion recognition is of great significance in …
EEG-based cross-subject emotion recognition using Fourier-Bessel series expansion based empirical wavelet transform and NCA feature selection method
A Anuragi, DS Sisodia, RB Pachori - Information Sciences, 2022 - Elsevier
Automated emotion recognition using brain electroencephalogram (EEG) signals is
predominantly used for the accurate assessment of human actions as compared to facial …
predominantly used for the accurate assessment of human actions as compared to facial …
Learning DenseNet features from EEG based spectrograms for subject independent emotion recognition
N Pusarla, A Singh, S Tripathi - Biomedical signal processing and control, 2022 - Elsevier
Subject-independent emotion recognition (SIER) using electroencephalogram (EEG)
signals has always been a challenge among the biomedical research community. One of the …
signals has always been a challenge among the biomedical research community. One of the …
Emotion recognition using effective connectivity and pre-trained convolutional neural networks in EEG signals
S Bagherzadeh, K Maghooli, A Shalbaf… - Cognitive …, 2022 - Springer
Abstract Convolutional Neural Networks (CNN) have recently made considerable advances
in the field of biomedical signal processing. These methodologies can assist in emotion …
in the field of biomedical signal processing. These methodologies can assist in emotion …
Classification of emotions using EEG activity associated with different areas of the brain
R Agarwal, M Andujar, S Canavan - Pattern Recognition Letters, 2022 - Elsevier
It is important that interactive Affective Brain-Computer Interface (aBCI) applications support
some degree of emotional intelligence. Many of the previous works that have explored the …
some degree of emotional intelligence. Many of the previous works that have explored the …
[PDF][PDF] Recognition of emotional states using EEG signals based on time-frequency analysis and SVM classifier.
FP George, IM Shaikat… - … of Electrical & …, 2019 - download.garuda.kemdikbud.go.id
The recognition of emotions is a vast significance and a high developing field of research in
the recent years. The applications of emotion recognition have left an exceptional mark in …
the recent years. The applications of emotion recognition have left an exceptional mark in …
Leveraging spatial-temporal convolutional features for EEG-based emotion recognition
Y An, N Xu, Z Qu - Biomedical Signal Processing and Control, 2021 - Elsevier
The electroencephalogram (EEG) signal is a medium to realize a brain–computer interface
(BCI) system due to its zero clinical risk and portable acquisition devices. As deep learning …
(BCI) system due to its zero clinical risk and portable acquisition devices. As deep learning …
Multi-method fusion of cross-subject emotion recognition based on high-dimensional EEG features
F Yang, X Zhao, W Jiang, P Gao, G Liu - Frontiers in computational …, 2019 - frontiersin.org
Emotion recognition using electroencephalogram (EEG) signals has attracted significant
research attention. However, it is difficult to improve the emotional recognition effect across …
research attention. However, it is difficult to improve the emotional recognition effect across …