Loading [a11y]/accessibility-menu.js
Generative Adversarial Networks for Electroencephalogram Signal Analysis: A Mini Review | IEEE Conference Publication | IEEE Xplore

Generative Adversarial Networks for Electroencephalogram Signal Analysis: A Mini Review


Abstract:

Brain-computer interface (BCI) technology based on electroencephalography (EEG) signals is growing rapidly and attracting widespread attention. However, due to the EEG ac...Show More

Abstract:

Brain-computer interface (BCI) technology based on electroencephalography (EEG) signals is growing rapidly and attracting widespread attention. However, due to the EEG acquisition methods, the quality and quantity of EEG signals are not able to be guaranteed. To alleviate the problems caused by the lack of data, in this paper, we introduce the applications of EEG signals using generative adversarial networks (GANs) which have shown great performance in image data augmentation and other time series data and then discuss their performance.
Date of Conference: 20-22 February 2023
Date Added to IEEE Xplore: 28 March 2023
ISBN Information:

ISSN Information:

Conference Location: Gangwon, Korea, Republic of

Funding Agency:


Contact IEEE to Subscribe

References

References is not available for this document.