Combining Genetic Algorithms and CNNs for Efficient Brain-machine Interface Systems: GA and CNNs for BMI Systems
Author:
Affiliation:
1. Graduate School of Science and Engineering, Hosei University,Tokyo,Japan
2. Hosei University,Department of Mechanical Engineering,Tokyo,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10402119/10402128/10402354.pdf?arnumber=10402354
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1. Performance analysis of LDA, QDA and KNN algorithms in left-right limb movement classification from EEG data
2. EEG classification using support vector machine
3. A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interface
4. Federated Transfer Learning for EEG Signal Classification
5. EEG based multi-class seizure type classification using convolutional neural network and transfer learning
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