STAFNet: an adaptive multi-feature learning network via spatiotemporal fusion for EEG-based emotion recognition

STAFNet: an adaptive multi-feature learning network via spatiotemporal fusion for EEG-based emotion recognition

IntroductionEmotion recognition using electroencephalography (EEG) is a key aspect of brain-computer interface research. Achieving precision requires effectively extracting and integrating both spatial and temporal features. However, many studies focus on a single dimension, neglecting the interplay...

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Bibliographic Details
Main Authors: Fo Hu, Kailun He, Mengyuan Qian, Xiaofeng Liu, Zukang Qiao, Lekai Zhang, Junlong Xiong
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-12-01
Series:Frontiers in Neuroscience
Subjects:
EEG
emotion recognition
deep learning
spatiotemporal fusion
adaptive adjacency matrix
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2024.1519970/full
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