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机译:基于关注机制的多尺度融合卷积神经网络,用于eEG信号解码的可视化机制
Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China;
Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China;
Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China;
Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China;
Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China;
Deep learning; Visualization; Feature extraction; Brain modeling; Electroencephalography; Decoding; Convolutional neural networks; BCI; MI; EEG; CNN; multi-brain regions; spatio temporal multi-scale features; dense fusion strategy; attention mechanism; visualization analysis;
机译:卷积神经网络用于对隐蔽注意力焦点和显着性图进行解码以实现EEG特征可视化
机译:与欧佩德解码和可视化的卷积神经网络深入学习
机译:使用卷积神经网络解码基于EEG的功能性大脑网络,具有不同的古代的严重性
机译:基于注意力驱动的卷积神经网络解码来自EEG信号的对象的视觉识别
机译:基于EEG信号的自回归建模和神经网络分析,设计用于监测麻醉深度的识别系统。
机译:使用卷积神经网络进行深度学习以进行EEG解码和可视化
机译:人体EEG信号中机器人动作成功的标志 观察者:使用深度卷积神经网络进行解码和可视化