The ability to capture fine spectral discriminative information enables hyperspectral images
(HSIs) to observe, detect and identify objects with subtle spectral discrepancy. However, the …

In this paper, we introduce a unified low-rank and sparse enhanced Tucker decomposition
model for tensor completion. Our model possesses a sparse regularization term to promote …

Image segmentation is of great importance in image processing. In this paper, we propose a
two-stage image segmentation strategy based on the nonconvex ℓ 2− ℓ p approximation of …

The internet traffic data completion is an important and challenging task in network
engineering. Due to the multi-dimensionality of internet traffic data, we introduce two tensor …

Matrix and tensor nuclear norms have been successfully used to promote the low-rankness
of tensors in low-rank tensor completion. However, singular value decomposition (SVD) …

By minimizing the tensor ranks, recent methods exploit the tensor spatial correlation
between the tensor entries for the low-rank tensor completion (TC) problem. However, these …

Recovery of network traffic data from incomplete observed data is an important issue in
internet engineering and management. In this paper, by fully combining the temporal …

Recent advances on low-rank representation have achieved promising performances for
tensor completion in the area of information sciences. However, current low-rank tensor …

Tensor robust principal component analysis (TRPCA) is an important method to handle high-
dimensional data and has been widely used in many areas. In this paper, we mainly focus …

Human motion capture (mocap) data records movement information from markers attached
to human joints and has been widely used in animation productions. However, due to lack of …