Evaluating the Performance of Some Deep Learning Model for the Problem of Emotion Recognition Based on EEG Signal
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-49529-8_19
Reference18 articles.
1. Yu, C., Wang, M.: Survey of Emotion Recognition Methods Using EEG Cognitive Robotics, vol. 2, pp. 132–146 (2022). ISSN 2667-2413https://doi.org/10.1016/j.cogr.2022.06.001
2. Houssein, E.H., Hammad, A., Ali, A.A.: Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review. Neural Comput. Appl.Comput. Appl. 34, 12527–12557 (2022). https://doi.org/10.1007/s00521-022-07292-4
3. Wang, X., Ren, Y., Luo, Z., He, W., Hong, J., Huang, Y.: Deep learning-based EEG emotion recognition: current trends and future perspectives. Front. Psychol. 27(14), 1126994 (2023). https://doi.org/10.3389/fpsyg.2023.1126994.PMID:36923142;PMCID:PMC10009917
4. Wang, J., Wang, M.: Review of the emotional feature extraction and classification using EEG signals. Cogn. Robot., 1 (2021).https://doi.org/10.1016/j.cogr.2021.04.001
5. Vempati, R., Sharma, L.: A systematic review on automated human emotion recognition using electroencephalogram signals and artificial intelligence. Results Eng. 18, 101027 (2023). https://doi.org/10.1016/j.rineng.2023.101027
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