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[HTML][HTML] Emotion recognition and artificial intelligence: A systematic review (2014–2023) and research recommendations
Emotion recognition is the ability to precisely infer human emotions from numerous sources
and modalities using questionnaires, physical signals, and physiological signals. Recently …
and modalities using questionnaires, physical signals, and physiological signals. Recently …
Automated emotion recognition: Current trends and future perspectives
Background Human emotions greatly affect the actions of a person. The automated emotion
recognition has applications in multiple domains such as health care, e-learning …
recognition has applications in multiple domains such as health care, e-learning …
A comprehensive survey on emotion recognition based on electroencephalograph (EEG) signals
Emotion recognition using electroencephalography (EEG) is becoming an interesting topic
among researchers. It has made a remarkable entry in the domain of biomedical, smart …
among researchers. It has made a remarkable entry in the domain of biomedical, smart …
[HTML][HTML] A systematic review on automated human emotion recognition using electroencephalogram signals and artificial intelligence
Abstract Brain-Computer Interaction (BCI) system intelligence has become more dependent
on electroencephalogram (EEG)-based emotion recognition because of the numerous …
on electroencephalogram (EEG)-based emotion recognition because of the numerous …
EEG-based cross-subject emotion recognition using Fourier-Bessel series expansion based empirical wavelet transform and NCA feature selection method
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 …
Ensemble machine learning-based affective computing for emotion recognition using dual-decomposed EEG signals
Machine learning (ML)-based algorithms have shown promising results in
electroencephalogram (EEG)-based emotion recognition. This study compares five …
electroencephalogram (EEG)-based emotion recognition. This study compares five …
PrimePatNet87: Prime pattern and tunable q-factor wavelet transform techniques for automated accurate EEG emotion recognition
Nowadays, many deep models have been presented to recognize emotions using
electroencephalogram (EEG) signals. These deep models are computationally intensive, it …
electroencephalogram (EEG) signals. These deep models are computationally intensive, it …
Temporal relative transformer encoding cooperating with channel attention for EEG emotion analysis
Electroencephalogram (EEG)-based emotion computing has become a hot topic of brain-
computer fusion. EEG signals have inherent temporal and spatial characteristics. However …
computer fusion. EEG signals have inherent temporal and spatial characteristics. However …
EEG emotion recognition based on TQWT-features and hybrid convolutional recurrent neural network
M Zhong, Q Yang, Y Liu, B Zhen, B **e - Biomedical signal processing …, 2023 - Elsevier
Electroencephalogram (EEG)-based emotion recognition has gained high attention in Brain-
Computer Interfaces. However, due to the non-linearity and non-stationarity of EEG signals …
Computer Interfaces. However, due to the non-linearity and non-stationarity of EEG signals …
A transformer based neural network for emotion recognition and visualizations of crucial EEG channels
JY Guo, Q Cai, JP An, PY Chen, C Ma, JH Wan… - Physica A: Statistical …, 2022 - Elsevier
With the rapid development of artificial intelligence and sensor technology,
electroencephalogram-based (EEG) emotion recognition has attracted extensive attention …
electroencephalogram-based (EEG) emotion recognition has attracted extensive attention …