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CORRECTION article

Front. Neurosci., 26 October 2022

Sec. Neural Technology

Volume 16 - 2022 | https://doi.org/10.3389/fnins.2022.1024150

Corrigendum: Multi-person feature fusion transfer learning-based convolutional neural network for SSVEP-based collaborative BCI

  • 1. School of Integrated Circuit Science and Engineering, Tianjin University of Technology, Tianjin, China

  • 2. Department of Computer and Network Engineering, College of Information Technology, UAE University, Al Ain, United Arab Emirates

  • 3. China Electronics Cloud Brain Technology Co., Ltd., Tianjin, China

  • 4. Key Laboratory of Complex System Control Theory and Application, Tianjin University of Technology, Tianjin, China

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In the published article, there was an error in the article title as published. Instead of “Steady-state visually evoked potential collaborative BCI system deep learning classification algorithm based on multi-person feature fusion transfer learning-based convolutional neural network,” it should be “Multi-person feature fusion transfer learning-based convolutional neural network for SSVEP-based collaborative BCI.”

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Summary

Keywords

steady-state visually evoked potential, collaborative BCI, feature fusion, convolutional neural network, transfer learning

Citation

Li P, Su J, Belkacem AN, Cheng L and Chen C (2022) Corrigendum: Multi-person feature fusion transfer learning-based convolutional neural network for SSVEP-based collaborative BCI. Front. Neurosci. 16:1024150. doi: 10.3389/fnins.2022.1024150

Received

21 August 2022

Accepted

12 October 2022

Published

26 October 2022

Volume

16 - 2022

Edited and reviewed by

Michele Giugliano, International School for Advanced Studies (SISSA), Italy

Updates

Copyright

*Correspondence: Longlong Cheng Chao Chen

This article was submitted to Neural Technology, a section of the journal Frontiers in Neuroscience

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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