机译:使用嵌套间隔无味卡尔曼滤波器和LSTM网络的嘈杂数据集基于手关节的手势识别
Marine Information Technology Laboratory (Ocean University of China), Ministry of Education,Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology;
Marine Information Technology Laboratory (Ocean University of China), Ministry of Education;
Marine Information Technology Laboratory (Ocean University of China), Ministry of Education,Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology;
School of Automation, China University of Geosciences,Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems;
Gesture recognition; Noisy dataset; NIUKF-LSTM; Hand joints;
机译:模糊规则和卡尔曼滤波器支持手势识别
机译:通过组合金字塔神经网络和双路无需卡尔曼滤波器来高效而快速的真实嘈杂的图像去噪
机译:无味卡尔曼滤波器在过滤噪声混沌信号中的非周期性现象
机译:基于卡尔曼滤波估计的手/手重叠的基于隐马尔可夫模型的手势识别
机译:无味卡尔曼滤波,用于相对姿态和位置估计。
机译:具有交互作用的无模型卡尔曼滤波器(IMM-UKF)算法和灰色神经网络的具有成本效益的车辆定位解决方案
机译:滤波噪声混沌信号的Unscented卡尔曼滤波器的收敛性分析
机译:Unscented卡尔曼滤波与Unscented schmidt卡尔曼滤波在预测地球同步卫星姿态和相关不确定性中的比较。