机译:多个非线性特征基于融合的驱动疲劳检测
Northeastern Univ Fac Robot Sci & Engn Shenyang 110169 Liaoning Peoples R China;
Northeastern Univ Fac Robot Sci & Engn Shenyang 110169 Liaoning Peoples R China;
Northeastern Univ Fac Robot Sci & Engn Shenyang 110169 Liaoning Peoples R China;
Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China;
Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China;
Northeastern Univ Fac Robot Sci & Engn Shenyang 110169 Liaoning Peoples R China;
Driving fatigue detection; EEG; Nonlinear feature; Features fusion; Multiple kernel learning;
机译:基于多特征融合和半监督主动学习的疲劳驾驶检测模型
机译:基于信息熵的特征融合来驱动疲劳检测
机译:基于特征级数据融合的基于非线性超声调制的疲劳裂纹检测的可靠性提高
机译:基于多特征融合的疲劳驾驶检测
机译:基于专用深度卷积网络的非线性扩散特征的增强面部活动度检测及其在OAuth中的应用。
机译:基于事件相关和视觉诱发电位的心理疲劳水平检测在虚拟室内环境中融合特征
机译:基于改进贝叶斯融合算法的疲劳驾驶检测闪烁数字预测