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A Teaching Framework Based on Big Data of Students’ Learning Behaviors: A Case Study of Academic Performance Prediction Read chapter Read first chapter

2023 | OriginalPaper | Chapter

GAN-Generated Data for BCI: Current State of Affairs and Challenges

Author : Eduardo Carabez

Published in: Frontier Computing

Publisher: Springer Nature Singapore

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Abstract

The performance of brain-computer interfaces highly depends on the quality and amount of data gathered and used to implement its classifier module. To facilitate the development of brain-computer interfaces, generative adversarial networks have been used in recent years and in various applications to generate data and complement real brain activity recordings obtained from subjects. As data acquisition often involves exhaustive experiment trials, artificially generating part of the necessary data can be seen as a milestone in the development of brain-computer interfaces but, nevertheless, this remains a rather uncommon practice. In this work, I discuss the challenges that might be keeping this practice from becoming widely used and propose a project focused on addressing some of those challenges.

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previous chapter Cooperative Learning Clustering in the Programming Courses
next chapter Communication-Efficient Federated Learning with Model Pruning
Literature
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Metadata
Title
GAN-Generated Data for BCI: Current State of Affairs and Challenges
Author
Eduardo Carabez
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Frontier Computing

Print ISBN: 978-981-9914-27-2

Electronic ISBN: 978-981-9914-28-9

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-99-1428-9_7