CMHFE-DAN: A Transformer-Based Feature Extractor with Domain Adaptation for EEG-Based Emotion Recognition

CMHFE-DAN: A Transformer-Based Feature Extractor with Domain Adaptation for EEG-Based Emotion Recognition

EEG-based emotion recognition (EEG-ER) through deep learning models has gained more attention in recent years, with more researchers focusing on architecture, feature extraction, and generalisability. This paper presents a novel end-to-end deep learning framework for EEG-ER, combining temporal featu...

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Bibliographic Details
Main Authors: Manal Hilali, Abdellah Ezzati, Said Ben Alla
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Information
Subjects:
emotion recognition
electroencephalogram signal (EEG)
domain adaptation
deep learning
convolutional neural network (CNN)
transformer-based architecture
Online Access:https://www.mdpi.com/2078-2489/16/7/560
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