Shitong Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Shitong Wang has a total of 45 co-authors. Here are the top co-authors by number of shared publications:
- Fu-Lai Chung
Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
16 shared publications - Jian-Wen Tao
Jiangnan University
4 shared publications Zhaohong Deng
Jiangnan University
4 shared publicationsDewen Hu
National University of Defense Technology
3 shared publicationsHu Dewen
National Defense University of Science and Technology Changsha
2 shared publications- Jun Wang
School of Communication and Information Engineering, Shanghai University, Shanghai, China
2 shared publications
Latest Publications
- 18 January 2014
- Published by Springer Nature
- p. 49-103
Novel Inductive and Transductive Transfer Learning Approaches Based on Support Vector Learning
- 18 January 2014
- Published by Springer Nature
- p. 49-103
Novel Inductive and Transductive Transfer Learning Approaches Based on Support Vector Learning
- 20 October 2013
- Published by China Science Publishing & Media Ltd. in Journal of Software
- Vol. 24 (10) , 2312-2326
Support Vector Regression for Large Domain Adaptation
- 20 October 2013
- Published by China Science Publishing & Media Ltd. in Journal of Software
- Vol. 24 (10) , 2312-2326
Support Vector Regression for Large Domain Adaptation
- 20 August 2013
- Published by China Science Publishing & Media Ltd. in Acta Automatica Sinica
- Vol. 39 (8) , 1295-1309
Kernel Distribution Consistency Based Local Domain Adaptation Learning
- 20 August 2013
- Published by China Science Publishing & Media Ltd. in Acta Automatica Sinica
- Vol. 39 (8) , 1295-1309
Kernel Distribution Consistency Based Local Domain Adaptation Learning
- 3 July 2013
- Published by Springer Nature in Pattern Analysis and Applications
- Vol. 17 (3) , 549-566
Double indices-induced FCM clustering and its integration with fuzzy subspace clustering
- 3 July 2013
- Published by Springer Nature in Pattern Analysis and Applications
- Vol. 17 (3) , 549-566
Double indices-induced FCM clustering and its integration with fuzzy subspace clustering
- Open Access
- 1 December 2012
- Published by SAGE Publications in Journal of Algorithms & Computational Technology
- Vol. 6 (4) , 639-652
Some Remarks on FCMLS with its Application to Foreground Extraction
It is well known that fuzzy clustering and level set are two important tools for image segmentation. The former focuses on analyzing the statistical characteristics of image features, while the latter aims to acquire the good geometrical continuity of segmentation boundaries. Obviously, two kinds of methods may be complement to each other. Inspired by this idea, a new level set model integrated with fuzzy c-means (FCM) clustering FCMLS has been presented in our previous studies. Compared with FCM and original level set methods, some remarkable characteristics and better performance have been demonstrated. In this paper, we mainly concern with the foreground extraction problem, wherein some extended works are also reported including detailed analysis on the convergence of FCMLS, multiregional FCMLS. Our research results indicate that FCMLS has good performance and is very worthful for foreground image extraction.
- 1 December 2012
- Published by SAGE Publications in Journal of Algorithms & Computational Technology
- Vol. 6 (4) , 639-652
Open AccessSome Remarks on FCMLS with its Application to Foreground Extraction
It is well known that fuzzy clustering and level set are two important tools for image segmentation. The former focuses on analyzing the statistical characteristics of image features, while the latter aims to acquire the good geometrical continuity of segmentation boundaries. Obviously, two kinds of methods may be complement to each other. Inspired by this idea, a new level set model integrated with fuzzy c-means (FCM) clustering FCMLS has been presented in our previous studies. Compared with FCM and original level set methods, some remarkable characteristics and better performance have been demonstrated. In this paper, we mainly concern with the foreground extraction problem, wherein some extended works are also reported including detailed analysis on the convergence of FCMLS, multiregional FCMLS. Our research results indicate that FCMLS has good performance and is very worthful for foreground image extraction.
- 3 October 2012
- Published by Elsevier in Neural Networks
- Vol. 36, 120-128
Scaling up minimum enclosing ball with total soft margin for training on large datasets
- 3 October 2012
- Published by Elsevier in Neural Networks
- Vol. 36, 120-128
Scaling up minimum enclosing ball with total soft margin for training on large datasets
- 20 September 2012
- Published by China Science Publishing & Media Ltd. in Journal of Software
- Vol. 23 (9) , 2297-2310
Multiple Kernel Local Leaning-Based Domain Adaptation
- 20 September 2012
- Published by China Science Publishing & Media Ltd. in Journal of Software
- Vol. 23 (9) , 2297-2310
Multiple Kernel Local Leaning-Based Domain Adaptation
- 16 August 2012
- Published by Elsevier in Applied Soft Computing
- Vol. 13 (1) , 116-127
A minimax probabilistic approach to feature transformation for multi-class data
- 16 August 2012
- Published by Elsevier in Applied Soft Computing
- Vol. 13 (1) , 116-127
A minimax probabilistic approach to feature transformation for multi-class data
- 20 June 2012
- Published by China Science Publishing & Media Ltd. in Journal of Software
- Vol. 23 (6) , 1458-1471
Large Margin and Minimal Reduced Enclosing Ball Learning Machine
- 20 June 2012
- Published by China Science Publishing & Media Ltd. in Journal of Software
- Vol. 23 (6) , 1458-1471
Large Margin and Minimal Reduced Enclosing Ball Learning Machine
- 20 May 2012
- Published by China Science Publishing & Media Ltd. in Acta Automatica Sinica
- Vol. 38 (5) , 797-811
Kernel Support Vector Machine for Domain Adaptation
- 20 May 2012
- Published by China Science Publishing & Media Ltd. in Acta Automatica Sinica
- Vol. 38 (5) , 797-811
Kernel Support Vector Machine for Domain Adaptation