Department of Computer-Integrated Technologies, Automation and Mechatronics, Kharkiv National University of Radio Electronics, Kharkiv, Ukraine;
Department of Computer-Integrated Technologies, Automation and Mechatronics, Kharkiv National University of Radio Electronics, Kharkiv, Ukraine;
Department of Computer-Integrated Technologies, Automation and Mechatronics, Kharkiv National University of Radio Electronics, Kharkiv, Ukraine;
Department of Computer-Integrated Technologies, Automation and Mechatronics, Kharkiv National University of Radio Electronics, Kharkiv, Ukraine;
Robot sensing systems; Classification algorithms; Gyroscopes; Micromechanical devices; Machine learning; Task analysis;
机译:使用机器学习和惯性传感器对步行过程中的下肢肌肉疲劳进行分类
机译:基于来自单个可穿戴惯性传感器的信号的机器学习算法可以检测步行的表面和年龄相关的差异
机译:自动化和机器人2018运动间谍振动能量收集传感器可以使用机器学习技术跟踪火车乘客Marzieh jalal Abadi-data61,Csiro,澳大利亚
机译:基于MEMS的惯性传感器信号和用于分类机器人运动的机器学习方法
机译:用于人体运动识别的信号处理和机器学习方法
机译:使用机器学习和惯性传感器对步行过程中的下肢肌肉疲劳进行分类
机译:使用机器学习方法对大脑活动中的情感先验评估进行分类