Explainable machine learning for memory-related decoding via TabNet and non-linear features-Reference-Cited by-同舟云学术

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Explainable machine learning for memory-related decoding via TabNet and non-linear features

Published:2022-02-21 Issue: Volume: Page:
ISSN:
Container-title:2022 10th International Winter Conference on Brain-Computer Interface (BCI)
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Author:

Mametkulov Maxim¹,Artykbayev Abay¹,Koishigarina Darina¹,Kenessova Amina¹,Razikhova Kamilla¹,Kang Taeho²,Wallraven Christian³,Fazli Siamac¹

Affiliation:

1. Nazarbayev University,Department of Computer Science,Nur-Sultan,Kazakhstan,010000

2. Korea University,Department of Brain and Cognitive Engineering,Seoul,South Korea,02855

3. Korea University,Department of Artificial Intelligence and the Department of Brain and Cognitive Engineering,Seoul,South Korea,02855

Funder

Nazarbayev University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9734304/9734309/09734816.pdf?arnumber=9734816

Reference41 articles.

1. Subject-independent mental state classification in single trials

2. A High Performance Spelling System based on EEG-EOG Signals With Visual Feedback

3. Emotion recognition system using brain and peripheral signals: Using correlation dimension to improve the results of EEG

4. Non-linear behaviour of human EEG: fractal exponent versus correlation dimension in awake and sleep stages

5. Automated cortical projection of EEG sensors: Anatomical correlation via the international 10–10 system

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1. Explainable artificial intelligence approaches for brain–computer interfaces: a review and design space;Journal of Neural Engineering;2024-08-01

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