机译:Grassmann多峰隐式特征选择
College of Computer Science, Zhejiang University, Hangzhou, China;
School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China;
College of Computer Science, Zhejiang University, Hangzhou, China;
College of Computer Science, Zhejiang University, Hangzhou, China;
College of Computer Science, Zhejiang University, Hangzhou, China;
College of Computer Science, Zhejiang University, Hangzhou, China;
Multimodal features; Feature selection; The grassmann manifold;
机译:基于基于Grassmann距离的特征选择方法对内瘤图像肿瘤息肉分类的影响
机译:组学数据表型识别的隐式特征选择
机译:强化学习的新特征选择方法:条件互信息揭示了隐式状态-奖励依赖性
机译:使用隐式功能增强多模式虚拟现实环境中的沉浸式对象表示
机译:基层歧管特征选择和模式识别的算法
机译:传感器类型轴和基于位置的融合以及可穿戴式身体传感器网络中多模式人类日常活动识别的特征选择
机译:强化学习的特征选择:通过条件互信息评估隐式状态 - 奖励依赖