PSPN: Pseudo-Siamese Pyramid Network for multimodal emotion analysis
Emotion recognition plays an important role in human life and healthcare. The EEG has
been extensively researched as an objective indicator of intense emotions. However, current …
been extensively researched as an objective indicator of intense emotions. However, current …
Emotion recognition from multiple physiological signals using intra-and inter-modality attention fusion network
L Gong, W Chen, M Li, T Zhang - Digital Signal Processing, 2024 - Elsevier
Recently, many studies have shown that integrating multiple modalities can more accurately
and robustly identify human emotions compared with a single modality. However, how to …
and robustly identify human emotions compared with a single modality. However, how to …
A novel feature fusion network for multimodal emotion recognition from EEG and eye movement signals
B Fu, C Gu, M Fu, Y Xia, Y Liu - Frontiers in Neuroscience, 2023 - frontiersin.org
Emotion recognition is a challenging task, and the use of multimodal fusion methods for
emotion recognition has become a trend. Fusion vectors can provide a more comprehensive …
emotion recognition has become a trend. Fusion vectors can provide a more comprehensive …
Dynamic Emotion-Dependent Network with Relational Subgraph Interaction for Multimodal Emotion Recognition
Multimodal Emotion Recognition in Conversations (MERC) is an important topic in human-
computer interaction. In the MERC task, conversations exhibit dynamic emotional …
computer interaction. In the MERC task, conversations exhibit dynamic emotional …
Tdfnet: Transformer-based deep-scale fusion network for multimodal emotion recognition
Z Zhao, Y Wang, G Shen, Y Xu… - IEEE/ACM Transactions …, 2023 - ieeexplore.ieee.org
As deep learning technology research continues to progress, artificial intelligence
technology is gradually empowering various fields. To achieve a more natural human …
technology is gradually empowering various fields. To achieve a more natural human …
Exploring Emotions in EEG: Deep Learning Approach with Feature Fusion
D Tasaouf Mridula, AA Ferdaus, TS Pias - medRxiv, 2023 - medrxiv.org
Emotion is an intricate physiological response that plays a crucial role in how we respond
and cooperate with others in our daily affairs. Numerous experiments have been evolved to …
and cooperate with others in our daily affairs. Numerous experiments have been evolved to …
Deep Feature Extraction and Attention Fusion for Multimodal Emotion Recognition
Z Yang, D Li, F Hou, Y Song… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recently, electroencephalogram (EEG)-based multimodal emotion recognition has emerged
as one of the research hotspots in affective computing. However, the existing methods tend …
as one of the research hotspots in affective computing. However, the existing methods tend …
Cross-modal Guiding Neural Network for Multimodal Emotion Recognition from EEG and Eye Movement Signals
B Fu, W Chu, C Gu, Y Liu - IEEE Journal of Biomedical and …, 2024 - ieeexplore.ieee.org
Multimodal emotion recognition research is gaining attention because of the emerging trend
of integrating information from different sensory modalities to improve performance …
of integrating information from different sensory modalities to improve performance …
Graph to Grid: Learning Deep Representations for Multimodal Emotion Recognition
Multimodal emotion recognition based on electroencephalogram (EEG) and compensating
physiological signals (eg, eye tracking) has shown potential in the diagnosis and …
physiological signals (eg, eye tracking) has shown potential in the diagnosis and …
TACOformer: Token-channel compounded cross attention for multimodal emotion recognition
X Li - arXiv preprint arXiv:2306.13592, 2023 - arxiv.org
Recently, emotion recognition based on physiological signals has emerged as a field with
intensive research. The utilization of multi-modal, multi-channel physiological signals has …
intensive research. The utilization of multi-modal, multi-channel physiological signals has …