Cross-Subject Transfer Method Based on Domain Generalization for Facilitating Calibration of SSVEP-based BCIs

Huang, J. orcid.org/0000-0002-0905-0915, Zhang, Z.-Q. orcid.org/0000-0003-0204-3867, Xiong, B. orcid.org/0000-0002-1150-2108 et al. (4 more authors) (2023) Cross-Subject Transfer Method Based on Domain Generalization for Facilitating Calibration of SSVEP-based BCIs. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31. 3307 -3319. ISSN 1558-0210

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Item Type: Article
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This item is protected by copyright. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.

Keywords: Brain-computer interfaces (BCIs), cross-subject, domain generalization, steady-state visual evoked potential (SSVEP), transfer learning
Dates:
  • Published: 22 August 2023
  • Published (online): 14 August 2023
  • Accepted: 10 August 2023
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 21 Aug 2023 14:12
Last Modified: 23 May 2024 15:24
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Identification Number: 10.1109/tnsre.2023.3305202
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