MOCNN: A Multiscale Deep Convolutional Neural Network for ERP-Based Brain-Computer Interfaces-Reference-Cited by-同舟云学术

MOCNN: A Multiscale Deep Convolutional Neural Network for ERP-Based Brain-Computer Interfaces

Published:2024-09 Issue:9 Volume:54 Page:5565-5576
ISSN:2168-2267
Container-title:IEEE Transactions on Cybernetics
language:
Short-container-title:IEEE Trans. Cybern.

Author:

Jin Jing¹^ORCID,Xu Ruitian¹^ORCID,Daly Ian²^ORCID,Zhao Xueqing¹^ORCID,Wang Xingyu¹,Cichocki Andrzej³^ORCID

Affiliation:

1. Key Laboratory of Smart Manufacturing in Energy Chemical Process, East China University of Science and Technology, Ministry of Education, Shanghai, China

2. Brain-Computer Interfacing and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex, Colchester, U.K.

3. Systems Research Institute, Polish Academy of Science, Warsaw, Poland

Funder

National Natural Science Foundation of China

STI 2030-Major Projects under

Shanghai Municipal Science and Technology Major Project

Project of Jiangsu Province Science and Technology Plan Special Fund in 2022 (Key Research and Development Plan Industry Foresight, Fundamental Research Fund for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221036/10646531/10521896.pdf?arnumber=10521896

Reference53 articles.

1. Brain-computer interface technology: a review of the first international meeting

2. Real-Time Deep Neurolinguistic Learning Enhances Noninvasive Neural Language Decoding for Brain–Machine Interaction

3. Effect of Stimulus Size in a Visual ERP-Based BCI under RSVP

4. Developing a Novel Tactile P300 Brain-Computer Interface With a Cheeks-Stim Paradigm

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