Cognitive-inspired deep learning models for aspect-based sentiment analysis: A retrospective overview and bibliometric analysis
As cognitive-inspired computation approaches, deep neural networks or deep learning (DL)
models have played important roles in allowing machines to reach human-like …
models have played important roles in allowing machines to reach human-like …
[HTML][HTML] Multimodal Emotion Recognition using visual, vocal and Physiological Signals: a review
The dynamic expressions of emotion convey both the emotional and functional states of an
individual's interactions. Recognizing the emotional states helps us understand human …
individual's interactions. Recognizing the emotional states helps us understand human …
[PDF][PDF] Multimodal integration in large language models: A case study with mistral llm
F Hamzah, N Sulaiman - 2024 - files.osf.io
This work presents significant advancements in the multimodal capabilities of the Mistral
8x7B model, a large language model designed with eight experts of seven billion …
8x7B model, a large language model designed with eight experts of seven billion …
[HTML][HTML] Automatic recognition of multiple emotional classes from EEG signals through the use of graph theory and convolutional neural networks
Emotion is a complex state caused by the functioning of the human brain in relation to
various events, for which there is no scientific definition. Emotion recognition is traditionally …
various events, for which there is no scientific definition. Emotion recognition is traditionally …
Physioformer: Integrating multimodal physiological signals and symbolic regression for explainable affective state prediction
Most affective computing tasks still rely heavily on traditional methods, with few deep
learning models applied, particularly in multimodal signal processing. Given the importance …
learning models applied, particularly in multimodal signal processing. Given the importance …
[PDF][PDF] Hands-On Fundamentals of 1D Convolutional Neural Networks—A Tutorial for Beginner Users.
I Cacciari, A Ranfagni - Applied Sciences (2076-3417), 2024 - iris.cnr.it
In recent years, deep learning (DL) has garnered significant attention for its successful
applications across various domains in solving complex problems. This interest has spurred …
applications across various domains in solving complex problems. This interest has spurred …
Emotion Recognition in Human-Machine Interaction and a Review in Interpersonal Communication Perspective
Emotions are fundamental to daily decision-making and overall wellbeing. Emotions are
psychophysiological processes that are frequently linked to human-machine interaction, and …
psychophysiological processes that are frequently linked to human-machine interaction, and …
Multimodal emotion recognition by fusing complementary patterns from central to peripheral neurophysiological signals across feature domains
Z Ma, A Li, J Tang, J Zhang, Z Yin - Engineering Applications of Artificial …, 2025 - Elsevier
The implementation and application of artificial intelligence are propelling various advanced
affective computing frameworks. Automatic recognition of emotions using multimodal …
affective computing frameworks. Automatic recognition of emotions using multimodal …
Correlation mining of multimodal features based on higher-order partial least squares for emotion recognition in conversations
In fields requiring an understanding of emotions, such as digital human interaction and
public opinion analysis, achieving a dependable and interpretable model for mining …
public opinion analysis, achieving a dependable and interpretable model for mining …
Analysis of emotions of online car-hailing drivers under different driving conditions and scenarios
Emotion is an important factor that affects driving behavior, and thus, drivers' emotions are
closely related to overall traffic safety. We investigated the emotional expressions of online …
closely related to overall traffic safety. We investigated the emotional expressions of online …