EEG Data Augmentation for Emotion Recognition with a Task-Driven GAN
The high cost of acquiring training data in the field of emotion recognition based on electroencephalogram (EEG) is a problem, making it difficult to establish a high-precision model from EEG signals for emotion recognition tasks. Given the outstanding performance of generative adversarial networks...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-02-01
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Series: | Algorithms |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4893/16/2/118 |