A systematic review on affective computing: Emotion models, databases, and recent advances
Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …
EEG based emotion recognition: A tutorial and review
Emotion recognition technology through analyzing the EEG signal is currently an essential
concept in Artificial Intelligence and holds great potential in emotional health care, human …
concept in Artificial Intelligence and holds great potential in emotional health care, human …
Deep learning-based multimodal emotion recognition from audio, visual, and text modalities: A systematic review of recent advancements and future prospects
S Zhang, Y Yang, C Chen, X Zhang, Q Leng… - Expert Systems with …, 2023 - Elsevier
Emotion recognition has recently attracted extensive interest due to its significant
applications to human-computer interaction. The expression of human emotion depends on …
applications to human-computer interaction. The expression of human emotion depends on …
A novel bi-hemispheric discrepancy model for EEG emotion recognition
Neuroscience study has revealed the discrepancy of emotion expression between the left
and right hemispheres of human brain. Inspired by this study, in this article, we propose a …
and right hemispheres of human brain. Inspired by this study, in this article, we propose a …
From regional to global brain: A novel hierarchical spatial-temporal neural network model for EEG emotion recognition
In this paper, we propose a novel Electroencephalograph (EEG) emotion recognition
method inspired by neuroscience with respect to the brain response to different emotions …
method inspired by neuroscience with respect to the brain response to different emotions …
Differences first in asymmetric brain: A bi-hemisphere discrepancy convolutional neural network for EEG emotion recognition
Neuroscience research studies have shown that the left and right hemispheres of the human
brain response differently to the same or different emotions. Exploiting this difference in the …
brain response differently to the same or different emotions. Exploiting this difference in the …
A survey of textual emotion recognition and its challenges
Textual language is the most natural carrier of human emotion. In natural language
processing, textual emotion recognition (TER) has become an important topic due to its …
processing, textual emotion recognition (TER) has become an important topic due to its …
Comparison of different feature extraction methods for EEG-based emotion recognition
EEG-based emotion recognition is a challenging and active research area in affective
computing. We used three-dimensional (arousal, valence and dominance) model of emotion …
computing. We used three-dimensional (arousal, valence and dominance) model of emotion …
GMSS: Graph-based multi-task self-supervised learning for EEG emotion recognition
Previous electroencephalogram (EEG) emotion recognition relies on single-task learning,
which may lead to overfitting and learned emotion features lacking generalization. In this …
which may lead to overfitting and learned emotion features lacking generalization. In this …
Investigating EEG-based functional connectivity patterns for multimodal emotion recognition
Objective. Previous studies on emotion recognition from electroencephalography (EEG)
mainly rely on single-channel-based feature extraction methods, which ignore the functional …
mainly rely on single-channel-based feature extraction methods, which ignore the functional …