王卫卫，西安电子科技大学教授、博士生导师。分别于1993，1998和2001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。任中国数学会计算数学分会理事，曾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、深度学习、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3项。曾获陕西省科技奖1项，陕西高等学校科学技术研究优秀成果奖2项，陕西省电子学会优秀成果奖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》、《图像处理的多尺度分析方法》2部，在国内外重要学术期刊与会议上合作发表论文100余篇，SCI检索论文50余篇，发表期刊包括SIAM J. on Multiscale Modeling and Simulation，IEEE Trans. on Image Processing，IEEE Trans. On Circuits and Systems for Video Technology，Pattern Recognition，Signal Processing等。

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NME AND PRESENT POSITION

Weiwei Wang, Professor of Mathematics, PH.D advisor

E-mail   vivianwang919@126.com

 

RESEARCH INTERESTS

Image restoration              deep learning, variational methods, partial differential equations, sparse representation

Data Clustering                   deep learning, sparse representation          

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

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

 

Awards
• 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.

GRANTS
NSFC, 1/1/2009-31/12/2011, Cartoon+Texture Decomposition of Images
NSFC, 1/1/2015-31/12/2018, Image segmentation based on high-dimensional features and sparse subspace clustering

NSFC, 1/1/2019-31/12/2023, Image segmentation based on multiview subspace clustering

PUBLICATIONS

A. Books, Co-authored

X. Feng, W. Wang, Xixi Jia, Multiscale Methods for Image Processing, China Science Publishing&Media Ltd., (2024).

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

B. Selected Journal Paper

1. Xiaofang Li, Weiwei Wang*, Yu Han, Xiangchu Feng，Structure Aware Transfer Function Network for Low Light Image Enhancement, Engineering Applications of Artificial  Intelligence, 141 (2025) 109749.

2. Shengjiang Kong, Weiwei Wang*,  Noise Blind Deep Residual Wiener Deconvolution Network for Image Deblurring, Digital signal processing,  165 (2025) 105304.

3. Chuan Chen, Weiwei Wang*, Xixi Jia, Xiangchu Feng, Hanjia Wei,  Local Gaussian Ensemble for Arbitrary-Scale Image Super-Resolution, Computer Vision and Image Understanding, Volume 257, June 2025, 104372.

4. Shengjiang Kong， Weiwei Wang*， Yu Han， Xiangchu Feng，Noise Variances and Regularization Learning Gradient Descent Network for Image Deconvolution, Journal of Visual Communication and Image Representation，107 (2025) 104391

5. Chen Guan, Weiwei Wang, Haihong Ai , and Ravi P. Singh，A White-Box Module for Medical Image Multi-Classification via Bias Dendrite Net，IEEE Transactions on Instrumentation and measurement, 2025, 74: 5021712.

6. Hanjia Wei, Weiwei Wang, Xixi Jia∗, Xiangchu Feng, Chuan Chen，OMLK-Net: An Online Multi-scale Large Separable Kernel Distillation Network for efficient image super-resolution，Signal Processing, 237 (2025) 110078

7. Chunyu Yang，Weiwei Wang，Edge Enhancing Based Blind Kernel Estimation for Deep Image Deblurring，Circuits, Systems, and Signal Processing,(2025) 44:1017–1044

8. Wenhao Wu, Weiwei Wang*, Xixi Jia, Xiangchu Feng, Transformer Autoencoder for K-means Efficient clustering, Engineering Applications of Artificial Intelligence, 133 (2024) 108612.

9. Xiaofang Li, Weiwei Wang*, Xiangchu Feng, Min Li, Deep parametric Retinex decomposition model for low-light image enhancement, Computer Vision and Image Understanding, 2024(241):103948.

10. Ruolan Tang, Weiwei Wang*, Yu Han, Xiangchu Feng, Grownbb: Gromov–Wasserstein learning of neural best buddies for cross-domain correspondence,The Visual Computer, 2024

11. Yixing Ji, Shengjiang Kong, Weiwei Wang*, Xixi Jia, Xiangchu Feng, Iterative decoupling deconvolution network for image restoration, Journal of Visual Communication and Image Representation,104 (2024) 104288.

12. Xiaofang Li, Weiwei Wang*, Xiangchu Feng, Tingting Qi, Cartoon-Texture decomposition with patch-wise decorrelation, Journal of Visual Communication and Image Representation, 2023(90):103726.

13. Canlin Gan and Weiwei Wang*, Existence result for critical Klein-Gordon-Maxwell system involving steep potential well, AIMS mathematics, 2023.9, Volume 8, Issue 11: 26665-26681. 

14. S. Kong, W. Wang*, X.Feng, and X. Jia, Deep RED Unfolding Network for Image Restoration, IEEE Trans.on Image Processing, vol. 31, 2022, pp.852-867.

15. C.Yang, W.Wang*, X. Feng, Joint image restoration and edge detection in cooperative game formulation, Signal Processing, vol.191, 2022:108363.

16. W. Zhao, W. Wang*, X. Feng, Y. Han, A new variational method for selective segmentation of medical images, Signal Processing，190 (2022) :108292.

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

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

19. 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.

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

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

22. 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.

23. 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. 

24. 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.

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

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

27. 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.

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

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

30. 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.

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

32. X.Jia, X.Feng, W.Wang, Rank constrained nuclear norm minimization with application to image denoising, Signal Processing,  2016, 129: 1-11.

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

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

35. 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.

36. 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.

37. 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.

38. 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.

39. 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.

40. 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.

41. 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.

42. 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.

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

44. 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.

C. Selected Conference Paper

1. Weiwei Wang* and Haonan Deng，Efficient Unsupervised Clustering with Variational Information Bottleneck: A Fusion of Contrastive Learning and Alternating Optimization. In 2024 International Conference on Image Processing, Multimedia Technology and Maching Learning (IPMML 2024), December 27–29, 2024, Dali, China. ACM, New York, NY, USA, 7 pages. http://doi.org/10.1145/3722405.3722441

2. Wenhao Wu; Weiwei Wang*; Shengjiang Kong; Deep Structure and Attention aware Subspace Clustering  (DSASC), The 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, Xiamen, China, 2023-10-13- 2023-10-15.

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

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

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

6. 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

7. 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

8. 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.

9. 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.

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

11. 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.

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.

14. 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.

15. 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.