Spatial Variation Generation Algorithm for Motor Imagery Data Augmentation: Increasing the Density of Sample Vicinity-Reference-Cited by-同舟云学术

Spatial Variation Generation Algorithm for Motor Imagery Data Augmentation: Increasing the Density of Sample Vicinity

Published:2023 Issue: Volume:31 Page:3675-3686
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Qin Chengxuan¹^ORCID,Yang Rui¹^ORCID,Huang Mengjie²^ORCID,Liu Weibo³^ORCID,Wang Zidong³^ORCID

Affiliation:

1. School of Advanced Technology, Xi’an Jiaotong–Liverpool University, Suzhou, China

2. Design School, Xi’an Jiaotong–Liverpool University, Suzhou, China

3. Department of Computer Science, Brunel University London, Uxbridge, Middlesex, U.K

Funder

Jiangsu Provincial Qinglan Project

Science and Technology Program of Suzhou

Research Development Fund of Xi’an Jiaotong-Liverpool University

Natural Science Foundation of the Jiangsu Higher Education Institutions of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

Reference58 articles.

1. Data augmentation generative adversarial networks;antoniou;Proc 6th Int Conf Learn Represent (ICLR),2017

3. Dropout: A simple way to prevent neural networks from overfitting;srivastava;J Mach Learn Res,2014

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