Magdra: a multi-modal attention graph network with dynamic routing-by-agreement for multi-label emotion recognition
X Li, J Liu, Y Xie, P Gong, X Zhang, H He - Knowledge-Based Systems, 2024 - Elsevier
Multimodal multi-label emotion recognition (MMER) is a vital yet challenging task in affective
computing. Despite significant progress in previous works, there are three limitations:(i) …
computing. Despite significant progress in previous works, there are three limitations:(i) …
Multimodal sentiment analysis using deep learning and fuzzy logic: A comprehensive survey
Multimodal sentiment analysis (MSA) is the process of identifying sentiment polarities that
users may simultaneously display in text, audio, and video data. Sentiment analysis …
users may simultaneously display in text, audio, and video data. Sentiment analysis …
Trajectory prediction of seagoing ships in dynamic traffic scenes via a gated spatio-temporal graph aggregation network
X Zhang, J Liu, P Gong, C Chen, B Han, Z Wu - Ocean Engineering, 2023 - Elsevier
Accurate ship trajectory prediction is essential in maritime traffic control and safety, requiring
the consideration of complex spatial and temporal dependencies within trajectory data. Most …
the consideration of complex spatial and temporal dependencies within trajectory data. Most …
A radial basis deformable residual convolutional neural model embedded with local multi-modal feature knowledge and its application in cross-subject classification
J Li, Y Zhou, T Liu, TP Jung, X Wan, D Duan… - Expert Systems with …, 2024 - Elsevier
In the spatial cognition and emotion recognition tasks based on electroencephalography
(EEG), the signal information representation of the single modal is incomplete because of …
(EEG), the signal information representation of the single modal is incomplete because of …
MTFR: An universal multimodal fusion method through Modality Transfer and Fusion Refinement
X Guo, S Tian, L Yu, X He, Z Wang - Engineering Applications of Artificial …, 2024 - Elsevier
Multimodal learning has made great achievements in recent years. However, most of the
existing modal fusion methods capture cross-modal correlations in a single stage and are …
existing modal fusion methods capture cross-modal correlations in a single stage and are …
A Multimodal Sentiment Analysis Method based on Fuzzy Attention Fusion
Y Zhi, J Li, H Wang, J Chen… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Affective analysis is a technology that aims to understand human sentiment states, and it is
widely applied in human–computer interaction and social sentiment analysis. Compared to …
widely applied in human–computer interaction and social sentiment analysis. Compared to …
CE-DCVSI: Multimodal relational extraction based on collaborative enhancement of dual-channel visual semantic information
Y Gong, X Lv, Z Yuan, F Hu, Z Cai, Y Chen… - Expert Systems with …, 2025 - Elsevier
Visual information implied by the images in multimodal relation extraction (MRE) usually
contains details that are difficult to describe in text sentences. Integrating textual and visual …
contains details that are difficult to describe in text sentences. Integrating textual and visual …
MST-ARGCN: modality-squeeze transformer with attentional recurrent graph capsule network for multimodal sentiment analysis
C Hu, J Liu, X Li, M Li, H He - The Journal of Supercomputing, 2025 - Springer
Multimodal sentiment analysis (MSA) is a heat topic in the deep learning research. Despite
the progress in previous studies, existing methods based on multimodal transformer (MulT) …
the progress in previous studies, existing methods based on multimodal transformer (MulT) …
Energy Shuttle Graph Convolution for Multimodal Relation Recognition in Videos
F Xi, H Xue, S Wang, M Xia, S Guo - IEEE Access, 2024 - ieeexplore.ieee.org
The reasoning of social relationships between characters from visual information can assist
people in determining characters' roles and understanding the interaction patterns of …
people in determining characters' roles and understanding the interaction patterns of …
LEET: stock market forecast with long-term emotional change enhanced temporal model
The stock market serves as a macroeconomic indicator, and stock price forecasting aids
investors in analysing market trends and industry dynamics. Several deep learning network …
investors in analysing market trends and industry dynamics. Several deep learning network …