Fourier phase retrieval(PR) is a severely ill-posed inverse problem that...
Fourier phase retrieval (FPR) is a challenging task widely used in vario...
The randomized sparse Kaczmarz method, designed for seeking the sparse
s...
This paper proposes a regularizer called Implicit Neural Representation
...
The explicit low-rank regularization, e.g., nuclear norm regularization,...
The sketch-and-project, as a general archetypal algorithm for solving li...
Conventionally, the matrix completion (MC) model aims to recover a matri...
Protecting the Intellectual Property Rights (IPR) associated to Deep Neu...
The randomized sparse Kaczmarz method was recently proposed to recover s...
Graph Neural Networks(GNNs) are useful deep learning models to deal with...
It has been an important approach of using matrix completion to perform ...
This paper first reviews the reversible data hiding scheme, of Liu et al...
This paper revisits the reversible data hiding scheme, of Liu et al. in ...
There exist many zero quantized discrete cosine transform (QDCT) coeffic...
Data in mobile cloud environment are mainly transmitted via wireless noi...
A steganographer network corresponds to a graphic structure that the inv...
Phase retrieval problem has been studied in various applications. It is ...
In reversible data embedding, to avoid overflow and underflow problem, b...
The conventional reversible data hiding (RDH) algorithms often consider ...
Steganography aims to conceal the very fact that the communication takes...