王卫卫

个人信息:Personal Information

教授 博士生导师 硕士生导师

性别:女

毕业院校:西安电子科技大学

学历:博士研究生毕业

学位:博士学位

在职信息:在职

所在单位:信息与计算数学系

所属院系: 数学与统计学院

学科:应用数学 计算数学

联系方式:qq:1914764237

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个人简介:Personal Profile

王卫卫,西安电子科技大学教授、博士生导师。分别于199319982001年在西安电子科技大学应用数学系获得应用数学专业学士、硕士和博士学位。曾在澳大利亚悉尼大学、美国宾夕法尼亚大学、杜兰大学、新奥尔良大学、香港理工大学做访问研究。兼任陕西省计算数学学会副理事长(2014-2019)。主要研究方向:机器学习、图像处理的数学方法。主持完成国家自然科学基金面上项目2项。曾获陕西省科技奖1项。在科学出版社合作出版科研专著《图像处理的变分与偏微分方程方法》一部,在国内外重要学术期刊与会议上合作发表论文70余篇,SCI检索论文30余篇,发表期刊包括IEEE Trans. on Image ProcessingIEEE Trans. On Circuits and Systems for Video Technology, SIAM J. on Multiscale Modeling and SimulationPattern RecognitionSignal Processing




                            Resume

NAME AND PRESENT POSITION

Weiwei Wang, Professor of Mathematics


E-mail    vivianwang919@126.com

 

RESEARCH INTERESTS

Machine learning           Subspace clustering, with applications in computer vision and bio-medical informatics

Image segmentation         active contour/level set methods, image feature clustering

Image restoration              variational methods, partial differential equations, sparse representation


EDUCATIONAL BACKGROUND

Ph.D., Applied Mathematics, Xidian University, Xi’an, China, 2001

M.S., Applied Mathematics, Xidian University, Xi’an, China, 1998

B.S., Applied Mathematics, Xidian University, Xi’an, China, 1993

 

HONORS
The second prize for Science and Technology Awards of Colleges and Universities in Shaanxi Province, 2018
The second prize for distinguished textbook “Numerical Analysis”, Xidian University, 2015;
The first prize for high-quality teaching at Xidian University, 2014;
The first prize for outstanding research at Xidian University, 2003.


CONTRACTS AND GRANTS
NSFC
, 1/1/2009-31/12/2011, PI, Cartoon+Texture Decomposition of Images
NSFC, 1/1/2015-31/12/2011, PI, Image segmentation based on high-dimensional features and sparse subspace clustering


PUBLICATIONS
A. Books, Co-authored

X. Feng, W. Wang, Variational and PDE Methods for Image Processing, China Science Publishing&Media Ltd., (2008).

 

B. Selected Journal Paper

  1. C. Yang, W. Wang*, X. Feng, R. He, Group Discriminative least square regression for multicategory classification, Neurocomputing, 407(2020):175-184, 2020.5

  2. C. Yang, W. Wang*, X. Feng, Classification-Friendly Sparse Encoder and Label Transformation Learning, IEEE Access, Vol.8, pp.54494-54505, 2020.3

  3. H. Huang, C. Lu, L. Zhang, W. Wang*, Convergence and stability analysis of the half thresholding based few-view CT reconstruction, J. Inverse Ill-Posed Problems, May 31, 2020

  4. C. Yang, W. Wang*, X. Feng, X. Liu, Weighted l1 Method Noise Regularization for Image Deblurring, Signal Processing, 157, 2019:14-24

  5. X Jia, X Feng, W. Wang, et al. Online Schatten quasi-norm minimization for robust principal component analysis, Information Sciences, 476,83-94, 2019.

  6. Y. Li, Q. Zhao, X. Feng, W. Wang, R. Zhang, A. Yan, A variational image segmentation method exploring both intensity means and texture patterns, Signal Processing: Image Communication, 76:214-230, 2019

  7. H. Huang, W. Wang*, C. Lu, X. Feng, R. He, Side-information-induced reweighted sparse subspace clustering, J. of Industrial and Management Optimization, 2019.

  8. W. Wang*, C. Yang, H. Chen, and X. Feng, Unified Discriminative and Coherent Semi-Supervised Subspace Clustering, IEEE Trans. On Image Processing, 2018.5, 27(5):2461-2470.

  9. W. Wang*, B. Zhang, X. Feng, Subspace Segmentation by Correlation Adaptive Regression, IEEE Trans. On Circuits and Systems for Video Technology, 2018.10,28(10): 2612-2621.

  10. H. Chen, W. Wang*, X. Feng, Structured Sparse Subspace Clustering with Within-Cluster Grouping, Pattern Recognition 83 (2018):107–118.

  11. H. Chen, W. Wang*, X. Feng, R. He, Discriminative and coherent subspace clustering, Neurocomputing, 284 (2018):177–186.

  12. X. Jia, X. Feng, W. Wang, C. Xu, L. Zhang, Bayesian inference for adaptive low rank and sparse matrix estimation, Neurocomputing , 2018.2, 291 (2018) 71–83.

  13. X Jia, X Feng, W Wang, L Zhang. An extended variational image decomposition model for color image enhancement. Neurocompting.322,216-228,2018.

  14. W. Wang*, C. Wu, Image Segmentation by Correlation Adaptive Weighted Regression, Neurocomputing, Dec.6, 2017, vol.267, pp.426–435.

  15. B. Zhang, W. Wang*, X. Feng, Subspace Clustering with Sparsity and Grouping Effect, Mathematical Problems in Engineering, March 22, 2017.

  16. W. Wang*, S. Kong, A. Razi, X. Feng, Image regularity and fidelity measure with a two-modality potential function, Mathematical Problems in Engineering, Vol.2017 (2017).

  17. X. Jia, X. Feng, W. Wang, Rank constrained nuclear norm minimization with application to 

    image denoising [J].  Signal Processing, 2016, 129: 1-11.

  18. S. Wang, X. Feng, W. Wang. "Low-rank + Dual" Model Based Dimensionality Reduction[J]. Neurocomputing. Vol.178, pp.3-10,2016.2.

  19. X. Li, W. Wang*, X. Feng, et al., Image denoising via bidirectional low rank representation with cluster adaptive dictionary, IET Image Processing, 2016.10,10(12):952-961.

  20. C. Wu, W. Wang*, “Image segmentation by adaptive nonconvex local and global subspace representation,” J. Electron. Imaging 25(3), 033026 (2016).

  21. X. Feng, L. Luo, X. Jia, W. Wang, A-divide-and-conquer stochastic alterable direction image denoising method, Signal Processing, 108:90-101,2015.

  22. W. Wang*, D. Zhai, T. Li, X. Feng, Salient edge and region aware image retargeting, Signal Processing: Image Communication, vol. 29, pp.1223–1231,2014.8.

  23. X. Zhang, X. Feng, W. Wang, Two direction nonlocal model for image denoising, IEEE Trans. on Image Processing, vol.22, no.1, pp.408-412, 2013.

  24. X. Zhang, X. Feng, W. Wang, W. Xue, Edge Strength Similarity for Image Quality Assessment[J]. IEEEE Signal Processing Letters, vol. 20, no.4, pp.319-322, 2013.

  25. Y. Han, X. Feng, G. Baciu, W. Wang, Nonconvex sparse regularizer based speckle noise removal, Pattern Recognition, vol.46, no.3, pp.989-1001, 2013.

  26. X. Zhang, X. Feng, W. Wang, G. Liu. Image Denoising via 2D dictionary learning and adaptive hard thresholding [J]. Pattern Recognition Letters, vol.34, no.16, pp.2110-2117, 2013.

  27. X. Zhang, X. Feng, W. Wang, G. Liu, Two direction nonlocal model for imager interpolation[J]. SCIENCE CHINA, Technological series, vol.56, no.4, pp.930-939, 2013.

  28. X. Zhang, X. Feng, W. Wang, et al., Gradient based Wienner filter for image denoising, Computers & Electrical Engineering, vol.39, no.3, pp.934-944, 2013.

  29. Y. Han, W. Wang, X. Feng, A new fast multiphase image segmentation algorithm based on nonconvex regularizer, Pattern Recognition, vol.45, no. 1, pp.363-372, 2012.

  30. X. Feng, G. Liu, W. Wang, Iterative regularization and inverse scale space methods with wave atoms, Applicable Analysis, vol.90, no.8, pp.1215-1225, 2011.

  31. Y. Li, X. Feng, W. Wang, Color-dependent diffusion equations based on quaternion algebra, Chinese Journal of Electronics,2012, 20(2): 277-282.

  32. W Wang*, X. Feng, Anisotropic Diffusion with Nonlinear Structure Tensor, SIAM J. Multiscale modeling and simulation, 2008,7(2):963-977.

  33. W. Wang *, P. Shui, X. Feng. Variational models for fusion and denoising of multi-focus images. IEEE signal processing letters, 2008.7, 15(1):65-68.

  34. S. Zhou, W. Wang, L. Zhou. A New Technique for Generalized Learning Vector Quantization Algorithm. Image and Vision Computing, 2006, 24(7):649-655. 

C. Selected Conference Paper

  1. W. Wang*, C. Yang, Q. Li, Discriminative analysis dictionary and classifier learning for pattern classification, IEEE Inter. Conf. On Image Processing, Taibei, 2019

  2. C. Yang, W. Wang*, X. FengGroup discriminative least square regression, ISICDM2019, August 24-26, Xi’an, China, 324-329

  3. Q. Wang, W. Wang*, X. FengSubspace clustering by relaxed block diagonal representation, ISICDM2019, August 24-26, Xi’an, China, 343-348

  4. A. Razi, W. Wang*, X. Feng, Image Segmentation by Active Contour Model with a New Data Fidelity, 2017 International Conference on Machine Vision and Information Technology (CMVIT 2017), Singapore, March 16, 2017

  5. A. Razi, W. Wang*, X.Feng, An Active Contour Method Using Harmonic Mean, IEEE 2016 International Conference on Signal and Image Processing (ICSIP 2016), Beijing, China, 13-15 August 2016, pp.287-291

  6. X. Jia,  X Feng, W. Wang, Adaptive regularizer learning for low rank approximation with 

    application to image denoising [C] IEEE Inter. Conf. On Image Processing, 2016: 3096-3100.

  7. W. Wang*, C. Wu, H. Huang, X. Feng, Subspace Clustering by weighted correlation adaptive regression, Proceedings of the 2016 International Conference on Machine Learning and Cybernetics (ICMLC2016), Jeju, South Korea, 10-13 July 2016, pp.453-458.

  8. H. Chen, W. Wang*, C. ZHAO, H. Huang, Simultaneous Multiphase image segmentation and Cartoon-texture DecompositionProceedings of the 2016 International Conference on Wavelet Analysis and Pattern Recognition(ICWAPR2016), Jeju, South Korea, 10-13 July  2016, pp.230-235.

  9. X. Li, W. Wang*, A. Razi, T. Li, Nonconvex low-rank sparse factorization for image segmentation [C]. in Proceedings of the 11th International Conference on Computational Intelligence and Security, 2015, 227-230.

  10. Z. Li, W. Wang*, P. Shui, Parameter estimation and two-stage segmentation algorithm for the Chan –Vese model, IEEE Inter. Conf. On Image Processing, Atlanta, GA, USA, 8-11, Oct. 2006: 201-204.

  11. W. Wang*, P. Shui, G. Song, Multifocus image fusion in wavelet domain. IEEE Inter. Conf. on Machine Learning and Cybernetics, Xi’an, 2003.11, 5:2887-2890.

  12. Jing Li, Weiwei Wang*, Xiaoping Li. Image retargeting based on a new salient region detection method [C]. in Proceedings of the 11th International Conference on Computational Intelligence and Security, 2015, 179-182.

  13. Tao Li, Weiwei Wang*, Xiangchu Feng, Long Xu, Image Denoising Using Low-Rank Dictionary and Sparse Representation[C] 2014 International Conference on Computational Intelligence and Security (CIS'2014), November 15-16, 2014, Kunming, Yunnan Province, China. pp.228-232.



  • 教育经历Education Background
  • 工作经历Work Experience
  • 研究方向Research Focus
  • 社会兼职Social Affiliations
  • 机器学习
    深度学习
    稀疏表示理论与应用
    图像处理的变分和偏微分方程方法
    • 陕西省计算数学协会副理事长