Integrated Connectivity-based Stacking Ensemble Learning with GCNNs for EEG Representation
Author:
Affiliation:
1. Australian Artificial Intelligence Institute, University of Technology,CIBCI Lab, Faculty of Engineering and Information Technology,Sydney
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10371778/10371788/10371894.pdf?arnumber=10371894
Reference20 articles.
1. Motor imagery as a complementary technique for functional recovery after stroke: a systematic review
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3. Brain signals analysis based deep learning methods: Recent advances in the study of non-invasive brain signals;Essa;arXiv preprint,2021
4. Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface
5. EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Enhancing MI EEG Signal Classification With a Novel Weighted and Stacked Adaptive Integrated Ensemble Model: A Multi-Dataset Approach;IEEE Access;2024
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