In this paper, a novel tensor subspace learning algorithm, tensor locality discriminant projection, is proposed.
本文提出了一种新的张量子空间的学习算法:张量局部判别投影。
The main contributions of this paper are listed as follows. (1) An incremental tensor subspace learning based object tracking is presented.
主要研究内容包括:(1)提出一种增量式张量子空间学习的目标跟踪算法。
Representation the high-dimensional data in a low-dimensional subspace is one of the fundamental problems in data analysis, pattern recognition, machine learning, and computer vision.
在低维空间描述高维数据是数据分析、模式识别、机器学习、计算机视觉等领域的基础问题之一。
Representation the high-dimensional data in a low-dimensional subspace is one of the fundamental problems in data analysis, pattern recognition, machine learning, and computer vision.
在低维空间描述高维数据是数据分析、模式识别、机器学习、计算机视觉等领域的基础问题之一。
应用推荐