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A Compact and Interpretable Convolutional Neural Network for Cross-Subject Driver Drowsiness Detection from Single-Channel EEG.

, , , , , , and . CoRR, (2021)

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EEG-based Cross-Subject Driver Drowsiness Recognition with Interpretable CNN., , , , and . CoRR, (2021)EEG-based Evaluation of Mental Fatigue Using Machine Learning Algorithms., , , , , and . CW, page 276-279. IEEE, (2018)Real-time EEG-based user's valence monitoring., , , and . ICICS, page 1-5. IEEE, (2015)EEG-Based Cross-Subject Driver Drowsiness Recognition With an Interpretable Convolutional Neural Network., , , and . IEEE Trans. Neural Networks Learn. Syst., 34 (10): 7921-7933 (October 2023)EEG-based Recognition of Driver State Related to Situation Awareness Using Graph Convolutional Networks., , , , and . CW, page 180-187. IEEE, (2020)Subject-Independent Drowsiness Recognition from Single-Channel EEG with an Interpretable CNN-LSTM model., , , , , , and . CW, page 201-208. IEEE, (2021)Human Factors Assessment in VR-based Firefighting Training in Maritime: A Pilot Study., , , , , , , , , and . CW, page 157-163. IEEE, (2020)EEG-Based Cross-Subject Mental Fatigue Recognition., , , , and . CW, page 247-252. IEEE, (2019)A Compact and Interpretable Convolutional Neural Network for Cross-Subject Driver Drowsiness Detection from Single-Channel EEG., , , , , , and . CoRR, (2021)Inter-subject transfer learning for EEG-based mental fatigue recognition., , , , and . Adv. Eng. Informatics, (2020)