Wetland contains various ground objects with high spectral similarity. How to accurately
distinguish complex classes has become a challenge in wetland land cover classification. In …

Intelligent video surveillance is a vital technique in smart city construction, where detection
of surveillance objects is generally achieved by subtracting estimated background from the …

In this paper, we study the low-rank matrix optimization problem, where the loss function is
smooth but not necessarily convex, and the penalty term is a nonconvex (folded concave) …

Low rank matrix and tensor completion problems are to recover the incomplete two and
higher order data of low rank structures. The essential problem in the matrix and tensor …

For fault diagnosis of rolling bearings, it is generally difficult or even impossible to obtain
class labels of new working condition samples under actual variable working conditions …

Completing traffic data is a basic requirement for intelligent transportation systems.
However, completing spatiotemporal traffic data poses a significant challenge, especially for …

针对迭代软阈值投影算法中的软阈值函数收缩功能较差的问题, 提出了迭代p 阈值投影算法. 用p
阈值函数替换迭代软阈值投影算法中的软阈值函数, 对小系数的惩罚更大 …

Recently, low-rank tensor completion (LRTC) has attracted significant attention since it has
been applied in a wide variety of practical areas. Due to the edge-preserving and noise …

Due to the influence of data collection methods and external complex factors, missing traffic
data is inevitable. However, complete traffic information is a necessary input for route …

In this paper, we study the low-rank matrix optimization problem, where the penalty term is
the ℓp (0< ρ< 1) regularization. Inspired by the good performance of half thresholding …