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Semi-supervised pairwise transfer learning based on multi-source domain adaptation: A case study on EEG-based emotion recognition
C Ren, J Chen, R Li, W Zheng, Y Chen, Y Yang… - Knowledge-Based …, 2024 - Elsevier
Negative transfer mitigation in transfer learning and universal-model establishment are
crucial in electroencephalography (EEG)-based emotion recognition research. This study …
crucial in electroencephalography (EEG)-based emotion recognition research. This study …
FMLAN: a novel framework for cross-subject and cross-session EEG emotion recognition
P Yu, X He, H Li, H Dou, Y Tan, H Wu… - … Signal Processing and …, 2025 - Elsevier
Emotion recognition is significant in brain-computer interface (BCI) applications.
Electroencephalography (EEG) is extensively employed for emotion recognition because of …
Electroencephalography (EEG) is extensively employed for emotion recognition because of …
Contrastive Learning of EEG Representation of Brain Area for Emotion Recognition
S Dai, M Li, X Wu, X Ju, X Li, J Yang… - IEEE Transactions on …, 2025 - ieeexplore.ieee.org
Emotion recognition based on Electroencephalography (EEG) has demonstrated promising
effectiveness in recent years. However, challenges have been experienced, such as limited …
effectiveness in recent years. However, challenges have been experienced, such as limited …
EEG-based emotion recognition using graph convolutional neural network with dual attention mechanism
W Chen, Y Liao, R Dai, Y Dong… - Frontiers in Computational …, 2024 - frontiersin.org
EEG-based emotion recognition is becoming crucial in brain-computer interfaces (BCI).
Currently, most researches focus on improving accuracy, while neglecting further research …
Currently, most researches focus on improving accuracy, while neglecting further research …
[HTML][HTML] Domain adversarial learning with multiple adversarial tasks for EEG emotion recognition
X Ju, X Wu, S Dai, M Li, D Hu - Expert Systems with Applications, 2025 - Elsevier
Abstract Domain adaptation methods using electroencephalography (EEG) play an
important role in cross-subject emotion recognition. However, enhancing the generalizability …
important role in cross-subject emotion recognition. However, enhancing the generalizability …
MMDA: A Multimodal and Multisource Domain Adaptation Method for Cross-Subject Emotion Recognition From EEG and Eye Movement Signals
M Jiménez-Guarneros… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Multimodal emotion recognition from electroencephalogram (EEG) and eye movement
signals has shown to be a promising approach to provide more discriminative information …
signals has shown to be a promising approach to provide more discriminative information …
Interpretable Image Emotion Recognition: A Domain Adaptation Approach Using Facial Expressions
This paper proposes a feature-based domain adaptation technique for identifying emotions
in generic images, encompassing both facial and non-facial objects, as well as non-human …
in generic images, encompassing both facial and non-facial objects, as well as non-human …