What is he best known for?
The fields of study he is best known for:
- Mathematical analysis
- Artificial intelligence
- Algebra
His main research concerns Algorithm, Wavelet, Artificial intelligence, Image restoration and Computer vision.
His Algorithm research includes elements of Image, Numerical analysis and Minification.
His studies deal with areas such as Mathematical analysis and Iterative reconstruction as well as Wavelet.
Within one scientific family, Zuowei Shen focuses on topics pertaining to Pattern recognition under Artificial intelligence, and may sometimes address concerns connected to Bregman method and Noise measurement.
His Matrix study incorporates themes from Refinable function and Interior point method.
Zuowei Shen combines subjects such as Combinatorics and Rank with his study of Matrix norm.
His most cited work include:
- A Singular Value Thresholding Algorithm for Matrix Completion (3961 citations)
- Framelets: MRA-based constructions of wavelet frames☆☆☆ (668 citations)
- Affine Systems in L2(Rd): The Analysis of the Analysis Operator. (550 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Wavelet, Algorithm, Artificial intelligence, Mathematical analysis and Computer vision.
His Wavelet study combines topics in areas such as Regularization and Image restoration.
His studies in Algorithm integrate themes in fields like Inverse problem, Image, Mathematical optimization, Tomography and Iterative reconstruction.
His Mathematical analysis research is multidisciplinary, incorporating perspectives in Refinable function, Pure mathematics and Applied mathematics.
His Sparse approximation research includes themes of Matrix and Sparse matrix.
His Compressed sensing study combines topics from a wide range of disciplines, such as Background subtraction and Rank.
He most often published in these fields:
- Wavelet (43.18%)
- Algorithm (31.82%)
- Artificial intelligence (26.70%)
What were the highlights of his more recent work (between 2014-2021)?
- Wavelet (43.18%)
- Algorithm (31.82%)
- Image restoration (18.75%)
In recent papers he was focusing on the following fields of study:
Wavelet, Algorithm, Image restoration, Combinatorics and Artificial intelligence are his primary areas of study.
In the subject of general Wavelet, his work in Wavelet packet decomposition is often linked to Shot noise, thereby combining diverse domains of study.
Zuowei Shen integrates Algorithm with Optical field in his research.
Zuowei Shen interconnects Noise reduction, Numerical analysis, Mathematical analysis, Asymptotic analysis and Imaging science in the investigation of issues within Image restoration.
His research in Combinatorics intersects with topics in Hölder condition, Smoothness and Function.
His work deals with themes such as Machine learning, Computer vision and Pattern recognition, which intersect with Artificial intelligence.
Between 2014 and 2021, his most popular works were:
- Dictionary Learning for Sparse Coding: Algorithms and Convergence Analysis (112 citations)
- Image Restoration: Wavelet Frame Shrinkage, Nonlinear Evolution PDEs, and Beyond (51 citations)
- Image restoration: A wavelet frame based model for piecewise smooth functions and beyond (47 citations)
In his most recent research, the most cited papers focused on:
- Mathematical analysis
- Algebra
- Artificial intelligence
Zuowei Shen spends much of his time researching Image restoration, Wavelet, Algorithm, Combinatorics and Mathematical analysis.
His Wavelet research is under the purview of Artificial intelligence.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Data mining, Big data.
Sparse approximation is closely connected to Mathematical optimization in his research, which is encompassed under the umbrella topic of Algorithm.
His study in Combinatorics is interdisciplinary in nature, drawing from both Hölder condition, Lipschitz continuity and Product.
His research in Mathematical analysis focuses on subjects like Applied mathematics, which are connected to Nonlinear evolution, Frame based, Partial differential equation, Total variation model and Gravitational singularity.
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