Unlike face recognition, gait recognition does not require the cooperation of human targets,
making it an attractive research area in both academia and industry. While there has been …

Two main tasks in pattern recognition area are clustering and classification. Owing to their
different goals, traditionally these two tasks are treated separately. However, when label …

Graph-based dimensionality reduction (DR) methods have been applied successfully in
many practical problems, such as face recognition, where graphs play a crucial role in …

State of energy (SOE) estimation of lithium-ion batteries is the basis for electric vehicle range
prediction. To improve the estimation accuracy of SOE under complex dynamic operating …

In this paper, a novel supervised subspace learning algorithm, named local similarity and
diversity preserving discriminant projection (LSDDP), is presented. LSDDP defines two …

Recently the underlying sparse representation structure in high dimensional data has
received considerable attention in pattern recognition and computer vision. In this paper, we …

Recently the underlying sparse representation structure in high dimensional data has
attracted considerable interests in pattern recognition and computer vision. Sparse …

Laplacian Eigenmaps (LE) is a typical nonlinear graph-based (manifold) dimensionality
reduction (DR) method, applied to many practical problems such as pattern recognition and …

摘要为了有效提取人脸的非线性结构信息, 提出一种新的基于最大散度差的核判别局部保留投影
方法. 首先通过核函数将样本数据映射到高维特征空间, 计算特征空间中样本的散度矩阵 …

Spectral regression is a newly proposed method for dimensionality reduction, which is also
based on graph embedding but less time and space consuming. However, like many …