GJFusion: A channel-level correlation construction method for multimodal physiological signal fusion
Physiological signal based ubiquitous computing has garnered significant attention.
However, the heterogeneity among multimodal physiological signals poses a critical …
However, the heterogeneity among multimodal physiological signals poses a critical …
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 …
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 …
Incongruity-Aware Cross-Modal Attention for Audio-Visual Fusion in Dimensional Emotion Recognition
RG Praveen, J Alam - IEEE Journal of Selected Topics in Signal …, 2024 - ieeexplore.ieee.org
Multimodal emotion recognition has immense potential for the comprehensive assessment
of human emotions, utilizing multiple modalities that often exhibit complementary …
of human emotions, utilizing multiple modalities that often exhibit complementary …
Emotion recognition from multimodal physiological signals using a regularized deep fusion of kernel machine
These days, physiological signals have been studied more broadly for emotion recognition
to realize emotional intelligence in human–computer interaction. However, due to the …
to realize emotional intelligence in human–computer interaction. However, due to the …
Msaf: Multimodal split attention fusion
Multimodal learning mimics the reasoning process of the human multi-sensory system,
which is used to perceive the surrounding world. While making a prediction, the human …
which is used to perceive the surrounding world. While making a prediction, the human …
Audio-visual fusion network based on conformer for multimodal emotion recognition
Audio-visual emotion recognition aims to integrate audio and visual information for accurate
emotion prediction, which is widely used in real application scenarios. However, most …
emotion prediction, which is widely used in real application scenarios. However, most …
FusionAtt: deep fusional attention networks for multi-channel biomedical signals
Y Yuan, K Jia - Sensors, 2019 - mdpi.com
Recently, pervasive sensing technologies have been widely applied to comprehensive
patient monitoring in order to improve clinical treatment. Various types of biomedical signals …
patient monitoring in order to improve clinical treatment. Various types of biomedical signals …
Cross-attention is not enough: Incongruity-aware dynamic hierarchical fusion for multimodal affect recognition
Fusing multiple modalities has proven effective for multimodal information processing.
However, the incongruity between modalities poses a challenge for multimodal fusion …
However, the incongruity between modalities poses a challenge for multimodal fusion …