Emotion Classification Based on Transformer and CNN for EEG Spatial–Temporal Feature Learning

Emotion Classification Based on Transformer and CNN for EEG Spatial–Temporal Feature Learning

Objectives: The temporal and spatial information of electroencephalogram (EEG) signals is crucial for recognizing features in emotion classification models, but it excessively relies on manual feature extraction. The transformer model has the capability of performing automatic feature extraction; ho...

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Bibliographic Details
Main Authors: Xiuzhen Yao, Tianwen Li, Peng Ding, Fan Wang, Lei Zhao, Anmin Gong, Wenya Nan, Yunfa Fu
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Brain Sciences
Subjects:
EEG
emotion classification
transformer
CNN
multi-head attention
Online Access:https://www.mdpi.com/2076-3425/14/3/268

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https://www.mdpi.com/2076-3425/14/3/268

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