In recent years, low-rank based tensor completion, which is a higher order extension of
matrix completion, has received considerable attention. However, the low-rank assumption …

Different optical imaging techniques are based on different characteristics of light. By
controlling the abrupt phase discontinuities with different polarized incident light, a …

Low-rank tensor completion methods have been advanced recently for modeling sparsely
observed data with a multimode structure. However, low-rank priors may fail to interpret the …

In this paper, we propose a highly accurate inpainting algorithm which reconstructs an
image from a fraction of its pixels. Our algorithm is inspired by the recent progress of non …

In this paper, a data-driven position-aided approach is proposed to reduce the training
overhead in MIMO systems by leveraging side information and on-the-field measurements …

In tissue engineering, cells are generally cultured in biomaterials to generate three-
dimensional artificial tissues to repair or replace damaged parts and re-establish normal …

Convex optimization, rather than a non-convex approach, still play important roles in many
computer science applications because of its exactness and efficiency. In this paper, we …

This paper presents a new development in structural health monitoring (SHM) data
management, processing, and mining based on compressive sensing (CS) technique, which …

In this study, the authors propose an adaptive channel estimation algorithm for
asymmetrically clipped optical orthogonal frequency‐division multiplexing visible light …

This chapter introduces tensor methods that can be used for low-level vision tasks such as
inpainting, denoising, deblurring, and superresolution. The tensor modeling approaches can …