Výsledky vyhledávání - "Zhou, Xinliang"

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A Comprehensive Survey on EEG-Based Emotion Recognition: A Graph-Based Perspective

Autor: Liu, Chenyu, Zhou, Xinliang, Wu, Yihao, Ding, Yi, Zhai, Liming, Wang, Kun, Jia, Ziyu, Liu, Yang

Compared to other modalities, electroencephalogram (EEG) based emotion recognition can intuitively respond to emotional patterns in the human brain and, therefore, has become one of the most focused tasks in affective computing. The nature of emotion

Externí odkaz: http://arxiv.org/abs/2408.06027

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Graph Neural Networks in EEG-based Emotion Recognition: A Survey

Autor: Liu, Chenyu, Zhou, Xinliang, Wu, Yihao, Yang, Ruizhi, Wang, Zhongruo, Zhai, Liming, Jia, Ziyu, Liu, Yang

Compared to other modalities, EEG-based emotion recognition can intuitively respond to the emotional patterns in the human brain and, therefore, has become one of the most concerning tasks in the brain-computer interfaces field. Since dependencies wi

Externí odkaz: http://arxiv.org/abs/2402.01138

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EENED: End-to-End Neural Epilepsy Detection based on Convolutional Transformer

Autor: Liu, Chenyu, Zhou, Xinliang, Liu, Yang

Recently Transformer and Convolution neural network (CNN) based models have shown promising results in EEG signal processing. Transformer models can capture the global dependencies in EEG signals through a self-attention mechanism, while CNN models c

Externí odkaz: http://arxiv.org/abs/2305.10502

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EEG-based Sleep Staging with Hybrid Attention

Autor: Zhou, Xinliang, Liu, Chenyu, Xiao, Jiaping, Liu, Yang

Sleep staging is critical for assessing sleep quality and diagnosing sleep disorders. However, capturing both the spatial and temporal relationships within electroencephalogram (EEG) signals during different sleep stages remains challenging. In this

Externí odkaz: http://arxiv.org/abs/2305.09543

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An EEG Channel Selection Framework for Driver Drowsiness Detection via Interpretability Guidance

Autor: Zhou, Xinliang, Lin, Dan, Jia, Ziyu, Xiao, Jiaping, Liu, Chenyu, Zhai, Liming, Liu, Yang

Drowsy driving has a crucial influence on driving safety, creating an urgent demand for driver drowsiness detection. Electroencephalogram (EEG) signal can accurately reflect the mental fatigue state and thus has been widely studied in drowsiness moni

Externí odkaz: http://arxiv.org/abs/2304.14920

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Interpretable and Robust AI in EEG Systems: A Survey

Autor: Zhou, Xinliang, Liu, Chenyu, Wang, Zhongruo, Zhai, Liming, Jia, Ziyu, Guan, Cuntai, Liu, Yang

The close coupling of artificial intelligence (AI) and electroencephalography (EEG) has substantially advanced human-computer interaction (HCI) technologies in the AI era. Different from traditional EEG systems, the interpretability and robustness of

Externí odkaz: http://arxiv.org/abs/2304.10755

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