[HTML][HTML] A systematic survey on multimodal emotion recognition using learning algorithms
Emotion recognition is the process to detect, evaluate, interpret, and respond to people's
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
emotional states and emotions, ranging from happiness to fear to humiliation. The COVID-19 …
Emotion recognition from unimodal to multimodal analysis: A review
K Ezzameli, H Mahersia - Information Fusion, 2023 - Elsevier
The omnipresence of numerous information sources in our daily life brings up new
alternatives for emotion recognition in several domains including e-health, e-learning …
alternatives for emotion recognition in several domains including e-health, e-learning …
Multimodal emotion recognition using deep learning
SMSA Abdullah, SYA Ameen, MAM Sadeeq… - Journal of Applied …, 2021 - jastt.org
New research into human-computer interaction seeks to consider the consumer's emotional
status to provide a seamless human-computer interface. This would make it possible for …
status to provide a seamless human-computer interface. This would make it possible for …
Comparing recognition performance and robustness of multimodal deep learning models for multimodal emotion recognition
Multimodal signals are powerful for emotion recognition since they can represent emotions
comprehensively. In this article, we compare the recognition performance and robustness of …
comprehensively. In this article, we compare the recognition performance and robustness of …
Adaptive multimodal emotion detection architecture for social robots
J Heredia, E Lopes-Silva, Y Cardinale… - Ieee …, 2022 - ieeexplore.ieee.org
Emotion recognition is a strategy for social robots used to implement better Human-Robot
Interaction and model their social behaviour. Since human emotions can be expressed in …
Interaction and model their social behaviour. Since human emotions can be expressed in …
Driver emotion recognition with a hybrid attentional multimodal fusion framework
Negative emotions may induce dangerous driving behaviors leading to extremely serious
traffic accidents. Therefore, it is necessary to establish a system that can automatically …
traffic accidents. Therefore, it is necessary to establish a system that can automatically …
Hierarchical multimodal-fusion of physiological signals for emotion recognition with scenario adaption and contrastive alignment
J Tang, Z Ma, K Gan, J Zhang, Z Yin - Information Fusion, 2024 - Elsevier
The lack of complementary affective responses from both the central and peripheral nervous
systems could limit the performance of emotion recognition with the single-modal …
systems could limit the performance of emotion recognition with the single-modal …
Cross-modal guiding and reweighting network for multi-modal RSVP-based target detection
J Mao, S Qiu, W Wei, H He - Neural Networks, 2023 - Elsevier
Abstract Rapid Serial Visual Presentation (RSVP) based Brain–Computer Interface (BCI)
facilities the high-throughput detection of rare target images by detecting evoked event …
facilities the high-throughput detection of rare target images by detecting evoked event …
An attention-based hybrid deep learning model for EEG emotion recognition
Y Zhang, Y Zhang, S Wang - Signal, Image and Video Processing, 2023 - Springer
Emotion recognition based on electroencephalography (EEG) has received much attention
in recent years, and there is more and more research on emotion recognition utilizing deep …
in recent years, and there is more and more research on emotion recognition utilizing deep …
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 …