Cross-subject multimodal emotion recognition based on hybrid fusion
Multimodal emotion recognition has gained traction in affective computing research
community to overcome the limitations posed by the processing a single form of data and to …
community to overcome the limitations posed by the processing a single form of data and to …
A review of multimodal emotion recognition from datasets, preprocessing, features, and fusion methods
B Pan, K Hirota, Z Jia, Y Dai - Neurocomputing, 2023 - Elsevier
Affective computing is one of the most important research fields in modern human–computer
interaction (HCI). The goal of affective computing is to study and develop the theories …
interaction (HCI). The goal of affective computing is to study and develop the theories …
A snapshot research and implementation of multimodal information fusion for data-driven emotion recognition
With the rapid development of artificial intelligence and mobile Internet, the new
requirements for human-computer interaction have been put forward. The personalized …
requirements for human-computer interaction have been put forward. The personalized …
Behavioral and physiological signals-based deep multimodal approach for mobile emotion recognition
With the rapid development of mobile and wearable devices, it is increasingly possible to
access users' affective data in a more unobtrusive manner. On this basis, researchers have …
access users' affective data in a more unobtrusive manner. On this basis, researchers have …
HEU Emotion: a large-scale database for multimodal emotion recognition in the wild
J Chen, C Wang, K Wang, C Yin, C Zhao, T Xu… - Neural Computing and …, 2021 - Springer
The study of affective computing in the wild setting is underpinned by databases. Existing
multimodal emotion databases in the real-world conditions are few and small, with a limited …
multimodal emotion databases in the real-world conditions are few and small, with a limited …
Expression-EEG based collaborative multimodal emotion recognition using deep autoencoder
H Zhang - IEEE Access, 2020 - ieeexplore.ieee.org
Emotion recognition has shown many valuable roles in people's lives under the background
of artificial intelligence technology. However, most existing emotion recognition methods …
of artificial intelligence technology. However, most existing emotion recognition methods …
EEG-based multi-modal emotion recognition using bag of deep features: An optimal feature selection approach
Much attention has been paid to the recognition of human emotions with the help of
electroencephalogram (EEG) signals based on machine learning technology. Recognizing …
electroencephalogram (EEG) signals based on machine learning technology. Recognizing …
Multimodal emotion recognition using a hierarchical fusion convolutional neural network
Y Zhang, C Cheng, Y Zhang - IEEE access, 2021 - ieeexplore.ieee.org
In recent years, deep learning has been increasingly used in the field of multimodal emotion
recognition in conjunction with electroencephalogram. Considering the complexity of …
recognition in conjunction with electroencephalogram. Considering the complexity of …
Multimodal emotion recognition based on facial expressions, speech, and EEG
Goal: As an essential human-machine interactive task, emotion recognition has become an
emerging area over the decades. Although previous attempts to classify emotions have …
emerging area over the decades. Although previous attempts to classify emotions have …
A novel spatio-temporal convolutional neural framework for multimodal emotion recognition
Proposing a practical method for high-performance emotion recognition could facilitate
human–computer interaction. Among existing methods, deep learning techniques have …
human–computer interaction. Among existing methods, deep learning techniques have …