Überblick über die Klassifizierung von EEG-Signalen mit maschinellem Lernen und Deep-Learning-Techniken-Reference-Cited by-同舟云学术

Überblick über die Klassifizierung von EEG-Signalen mit maschinellem Lernen und Deep-Learning-Techniken

Published:2024 Issue: Volume: Page:177-204
ISSN:
Container-title:Fortschritte in der nicht-invasiven biomedizinischen Signalverarbeitung mit ML
language:de
Short-container-title:

Author:

Hassan Fatima,Hussain Syed Fawad

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-52856-9_7

Reference66 articles.

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2. F. Hassan, Applying Deep Learning Methods for EEG Classification - a Case Study of Epi Lepsy and Schizophrenia (Master Thesis, Faculty of Computer Science and Engineering, Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, 2022)

3. H. Akbulut, S. Güney, H.B. Çotuk, A.D. Duru, Classification of EEG signals using alpha and beta frequency power during voluntary hand movement, in Scientific Meeting on Electrical-Electronics & Biomedical Engineering and Computer Science (EBBT), vol. 2019, (2019), S. 1–4. https://doi.org/10.1109/EBBT.2019.8741944

4. N. Jatupaiboon, S. Pan-ngum, P. Israsena, Emotion classification using minimal EEG channels and frequency bands, in The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE), (2013), S. 21–24. https://doi.org/10.1109/JCSSE.2013.6567313

5. W. Peng, EEG preprocessing and Denoising, in EEG Signal Processing and Feature Extraction, ed. by L. Hu, Z. Zhang, (Springer, Singapore, 2019), S. 71–87. https://doi.org/10.1007/978-981-13-9113-2_5