Motor Imagery Decoding Using Ensemble Curriculum Learning and Collaborative Training
Author:
Affiliation:
1. Queen Mary University of London,School of Electronic Engineering and Computer Science
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10480442/10480443/10480476.pdf?arnumber=10480476
Reference40 articles.
1. A Multi-Branch Convolutional Neural Network with Squeeze-and-Excitation Attention Blocks for EEG-Based Motor Imagery Signals Classification
2. MIN2Net: End-to-End Multi-Task Learning for Subject-Independent Motor Imagery EEG Classification
3. Team cogitat at neurips 2021: Benchmarks for eeg transfer learning competition;Bakas;arXiv preprint arXiv:2202.03267,2022
4. Brain–computer interface robotics for hand rehabilitation after stroke: a systematic review
5. Improving Generalization of CNN-Based Motor-Imagery EEG Decoders via Dynamic Convolutions
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