Full Publication List, Prof. Ming Dong:

Books

  1. Xuanwen Luo and Ming Dong, “Distributed Fault-Tolerant Detection in Wireless Sensor Networks: Event and Faulty Sensor Detection,” Scholars' Press, 2013, ISBN: 978-3639706109.
  2. Manjeet Rege and Ming Dong, “A Graph Theoretic approach to Heterogeneous Data Clustering: New Research Directions and Some Results,” VDM Verlag, 2010, ISBN: 978-3-639-11658-8.

Journal Articles

2018

  1. F. Zhang, Q. Mao, Y. Zhan and M. Dong, "Cascaded Multi-level Transformed Dirichlet Process for Multi-pose Facial Expression Recognition", The Computer Journal, in press, 2018.

  2. F. Zhang, Q. Mao, X. Shen, Y. Zhan and M. Dong, "Spatially Coherent Feature Learning for Pose-invariant Facial Expression Recognition", ACM Transactions on Multimedia Computing, Communications and Applications, in press, 2018.

  3. S. Chen, C. Zhang and M. Dong, “Deep Age Estimation: From Classification to Ranking”, IEEE Trans. on Multimedia, in press, 2018.

  4. Wang, L, Zhu, D and Dong, M, "Clustering over-dispersed data with mixed feature types", Statistical Analysis and Data Mining, in press, 2018

  5. X. Li, D. Zhu and M. Dong, “Multinomial classification with class-conditional overlapping sparse feature groups”, Pattern Recognition Letters, vol. 101, pp 37-43, Jan. 2018.

2017

  1. Qirong Mao, Yongbin Yu, Feifei Zhang, and Ming Dong, “Hierarchical Bayesian Theme Models for Multi-pose Facial Expression Recognition”, IEEE Trans. on Multimedia, Vol. 19, Issue 2, pp. 861-873, 2017.

  2. R. Almomani, M. Dong, and D. Zhu, “Object Tracking via Dirichlet Process-based Appearance Models”, Neural Computing and Applications, Special issues on Computational Intelligence for Vision and Robotics, Volume 28, Issue 5, pp 867–879, 2017.

2016 and Earlier

  1. Mehedi Hasan, Alexander Kotov, April Carcone, Ming Dong, Sylvie Naar, and Kathryn Brogan Hartlieb, “A study of the effectiveness of machine learning methods for classification of clinical interview fragments into large number of categories”, Journal of Biomedical Informatics, Volume 62, pp. 21-31, August 2016.

  2. L. Wang and M. Dong, "Exemplar-based Low-rank Matrix Decomposition for Data Clustering", Journal of Data Mining and Knowledge Discovery, Volume 29, Issue 2, pp 324-357, March 2015.

  3. Q. Mao, M. Dong, Z. Huang, and Y. Zhan, “Learning Salient Features for Speech Emotion Recognition Using Convolutional Neural Networks”, IEEE Trans. on Multimedia, Vol. 16, Issue 8, pp. 2203 – 2213, December 2014.

  4. L. Wang and M. Dong, “Multi-Level Low-rank Approximation-based Spectral Clustering for Image Segmentation”, Pattern Recognition Letters, Vol. 33, pp. 2206 - 2215, 2012.

  5. L. Wang, M. Rege, M. Dong, and Y. Ding “Low-rank Kernel Matrix Factorization for Large Scale Evolutionary Clustering”, IEEE Transactions on Knowledge and Data Engineering, Vol. 24, No. 6, pp 1036-1050, 2012.

  6. Y. Chen, L. Wang, and M. Dong, “Non-negative Matrix Factorization for Semi-supervised Heterogeneous Data Co-clustering”, IEEE Transactions on Knowledge and Data Engineering, Vol. 22, No. 10, pp. 1459-1474, October 2010.

  7. Mostafa Ghannad-Rezaie, Hamid Soltanian-Zadeh, Hao Ying, and Ming Dong, "Selection-Fusion Approach for Classification of Datasets with Missing Values", Pattern Recognition, Vol. 43, No. 6, 2340-2350, June 2010.

  8. Y. Chen, L. Wang, M. Dong and J. Hua, “Exemplar-based Visualization of Large-scale Text Corpus”, IEEE Transactions on Visualization and Computer Graphics, Vol. 15, No. 6, pp. 1193-1200, 2009.

  9. Zou, Z. Lai, J. Hua, X. Gu, and M. Dong, “Intrinsic Geometric Scale Space by Shape Diffusion”, IEEE Transactions on Visualization and Computer Graphics, Vol. 15, No.6, pp. 1161-1168, 2009.

  10. Y. Li, M. Dong, and J. Hua, “Simultaneous Localized Feature Selection and Model Detection for Gaussian Mixtures”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 31, No. 5, pp 953 - 960, 2009.

  11. Jing Hua, Zhaoqiang Lai, Ming Dong, Xianfeng Gu, and Hong Qin. "Geodesic Distance-Weighted Shape Diffusion", IEEE Transactions on Visualization and Computer Graphics, Vol. 14, No. 6, pp. 1643 – 1650, 2008.

  12. Guangyu Zou, Jing Hua, Ming Dong, and Hong Qin. "Surface Matching with Salient Keypoints in Geodesic Scale Space," Journal of Computer Animation and Virtual Worlds (formerly known as Journal of Visualization and Computer Animation), Vol. 19, pp. 399 - 410, 2008.

  13. Y. Chen, M. Rege, M. Dong, and J. Hua, “Non-negative Matrix Factorization for Semi-supervised Data Clustering”, Journal of Knowledge and Information Systems (Springer), Vol. 17, No. 3, pp. 355- 379, 2008 (invited as a best paper of ICDM 07).

  14. M. Rege, M. Dong, and F. Fotouhi, “Bipartite Isoperimetric Graph Partitioning for Data Co-clustering”, Data Mining and Knowledge Discovery (Springer), Vol. 16, No. 3, pp. 276-312, 2008.

  15. M. Dong and X. Zhou, “Knowledge Discovery in Corporate Events by Neural Network Rule Extraction”, Applied Intelligence, Special Issue on Soft Computing Techniques Applied to Finance, Vol. 29, pp. 129-137, 2008.

  16. Y. Li, M. Dong, and J. Hua “Localized Feature Selection for Clustering”, Pattern Recognition Letters, Vol. 29, pp. 10 - 18, 2008.

  17. Y. Li, M. Dong, and J. Hua, "A Gaussian Mixture Model to Detect Clusters Embedded in Feature Subspace", Journal of Communications in Information and Systems, Vol. 7, No. 4, pp. 337 - 352, 2007.

  18. Y. Tan, J. Hua, and M. Dong “3D Reconstruction from 2D Images with Hierarchical Continuous Simplicies,” The Visual Computer, Vol. 23, pp. 905 - 914, 2007.

  19. Jing Jiang, E. Mark Haacke, and Ming Dong “The Dependence of Vessel Area Accuracy and Precision as A Function of MR Imaging Parameters and Analysis Procedure", Journal of MRI, Vol. 25, pp. 1226- 1234, 2007.

  20. M. Rege, M. Dong, and F. Fotouhi, "Building a User-Centered Semantic Hierarchy in Image Databases", ACM Multimedia Systems Journal, Special Issue on User-Centered Multimedia, Vol. 12, No. 4, pp. 325- 338, 2007.

  21. C. Yang, M. Dong, and F. Fotouhi, "S-IRAS: an interactive Semantic Image Retrieval and Annotation System", International Journal on Semantic Web and Information Systems, Special Issue on Multimedia Semantics, Vol. 2, No. 3, pp. 37 - 54, 2006.

  22. Gulsheen Kaur, Jun Tan, Mohammed Alam, Vipin Chaudhary, Dingguo Chen, Ming Dong, Hazem Eltahawy, Farshad Fotouhi, Christopher Gammage, Jason Gong, William Grosky, Murali Guthikonda, Jingwen Hu, Devkanak Jeyaraj, Xin Jin, Albert King, Joseph Landman, Jong Lee, Qing Hang Li, Hanping Lufei, Michael Morse, Jignesh Patel, Ishwar Sethi, Weisong Shi, King Yang, and Zhiming Zhang, “CASMIL: A comprehensive software/toolkit for Image-guided Neurosurgeries”, International Journal of Medical Robotics and Computer Assisted Surgery, John Wiley & Sons Ltd., Vol. 2, No. 2, pp. 118—130, June 2006.

  23. X. Luo, M. Dong, and Y. Huang, “On Distributed Fault-Tolerant Detection in Wireless Sensor Networks”, IEEE Transactions on Computers, Volume 55, Number 1, pp. 58-70, January 2006.

  24. Y. Li, M. Dong, and R. Kothari, “Classifiability Based Omnivariate Decision Trees”, IEEE Transactions on Neural Networks, Volume 16, Number 6, pp. 1547 – 1560, November 2005.

  25. Rajeev Agrawal, Farshad Fotouhi, Peter Stanchev, and Ming Dong, “MPEG-7 Based Image Retrieval On The World Wide Web”, International Journal of Information Theories and Applications, Vol. 11, No. 2, pp. 112 – 120, 2004.

  26. M. Johnson, F. Fotouhi, S. Draghici, M. Dong, and X. Duo, “Discovering Document Semantics QBYS: a System for Querying the WWW by Semantics”, Multimedia Tools and Applications, Vol. 24, pp. 155--188, 2004.

  27. Xu-shen Zhou and M. Dong, "Can Fuzzy Logic Make Technical Analysis 20/20?” Financial Analysts Journal, Vol. 60, No. 4, pp. 54--75, July/August 2004.

  28. M. Dong and R. Kothari, "Feature Subset Selection Using a New Definition of Classifiability", Pattern Recognition Letters, Vol. 23, pp. 1215--1225, 2003.

  29. Shiyong Lu, Ming Dong, and Farshad Fotouhi, "The Semantic Web: Opportunities and Challenges for Next-Generation Web Applications", International Journal of Information Research, Vol. 7, No. 4, Special Issue on the Semantic Web. 2002.

  30. M. Dong and R. Kothari, "Look-Ahead Based Fuzzy Decision Tree Induction", IEEE Transactions on Fuzzy System, Vol. 9, No. 3, pp. 461--468, 2001.

Conference Papers

2018

  1. Elizabeth Towner, Lu Wang, Ming Dong and Dongxiao Zhu, "Using Multi-Task Learning to Develop Risk Profiles for Reducing Preschool Obesity Health Inequities", 39th Annual Meeting and Scientific Sessions of the Society of Behavioral Medicine, one-page abstract, New Orleans, Louisiana, April 2018.

  2. Haotian Xu, Ming Dong, Yasuo Nakai, Eishi Asano, and Jeong-Won Jeong, "Automatic Detection of Eloquent Axonal Pathways in Diffusion Tractography Using Intracanial Electrical Stimulation Mapping and Convolutional Neural Networks", Prof. of IEEE International Symposium on Biomedical Imaging (ISBI), Washington DC, April 2018.

  3. Lu Wang, Dongxiao Zhu, Elizabeth Towner and Ming Dong, "Obesity Risk Factors Ranking Using Multi-Task Learning", Prof. of IEEE Conference on Biomedical and Health Informatics, Las Vegas, NV, March 2018.

  4. Mehedi Hasan, Alexander Kotov, April Idalski Carcone, Ming Dong, Sylvie Naar, "Predicting the Outcome of Patient-Provider Communication Sequences using Recurrent Neural Networks and Probabilistic Models", AMIA Infomatics Summit, San Francisco, CA, March 2018

  5. Xinpeng L. Liao, Chengcui Zhang, Ming Dong and Xin Chen, "Deep Structured Prediction: A New Formulation for Person Re-Identification", Proc. of IEEE International Conference on Multimedia Information Processing and Retrieval, Miami, FL, April 2018.

  6. Nelson Ruwa, Qirong Mao and M. Dong, "Affective Visual Question Answering Network", Proc. of IEEE International Conference on Multimedia Information Processing and Retrieval, Miami, FL, April 2018.

2017

  1. Wang, L, Zhu, D, Li, Y and Dong, M, "Modeling Over-dispersion for Network Data Clustering", Proc. of IEEE International Conference on Machine Learning and Application, Cancun, Mexico, December 2017.

  2. H. Xu, M. Dong and Z. Zhong, "Directionally Convolutional Networks for 3D Shape Segmentation", Prof. of IEEE International Conference on Computer Vision (IEEE ICCV), Venice, Italy, October 2017.

  3. S. Chen, C. Zhang, M. Dong, J. Le and M. Rao “Ranking-CNN for Age Estimation”, Proc. of IEEE Conference on Computer Vision and Pattern Recognition (IEEE CVPR), Honolulu, Hawaii, July 2017.

  4. Xiaoce Feng, Yong Xu, Ming Dong and Philip Levy, “Non-contact Home Health Monitoring based on Low-cost High-performance Accelerometers”, Proc. of IEEE/ACM conference on connected health: Applications, Systems and Engineering Technologies, Philadelphia, PA, July 2017.

  5. Shixing Chen, Ming Dong, Jerry Le and Mike Rao, "A Method for Vehicle Occupant Height Estimation", Proc. of SAE World Congress & Exhibition, Detroit, MI, 2017.

  6. X. Li, D. Zhu, M. Dong, P. Levy and M. Nezhad, “SDT: A Tree Method for Detecting Patient Subgroups with Personalized Risk Factors”, Proc. of AMIA Joint Summits on Translational Science, San Francisco, CA, 2017.

2016

  1. Zhang, Q. Mao, M. Dong and Y. Zhan, “Multi-pose Facial Expression Recognition Using Transformed Dirichlet Process”, Proc. of ACM Conference on Multimedia (ACM MM), Amsterdam, Netherland, 2016.

  2. H. Xu, M. Dong, D. Zhu, A. Kotov, A. Carcone and S. Naar-King, “Text Classification with Topic-based Word Embedding and Convolutional Neural Networks”, Proc. of ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), Seattle, WA, 2016.

  3. Lu Wang, Dongxiao Zhu, Yan Li and Ming Dong, “Poisson-Markov Mixture Model and Parallel Algorithm for Binning Massive and Heterogeneous DNA Sequencing Reads”, International Symposium on Bioinformatics Research and Applications, Minsk, Belarus, June 2016.

  4. Carcone, A. Kotov, M. Hasan, H. Xu, M. Dong, S. Naar-King and K. Brogan, “Accelerating the Pace of Qualitative Communication Research with Computational Technology", 37th Annual Meeting and Scientific Sessions of the Society of Behavioral Medicine, Washington DC, 2016 (abstract).

  5. R. Almomani, M. Dong and D. Zhu, “A Bayesian Hierarchical Appearance Model for Robust Object Tracking”, Proc. of International Conference on Multimedia and Expo, Seattle, WA, 2016.

2015 and Earlier

  1. L. Wang, M. Dong and A. Kotov, “Multi-level Approximate Spectral Clustering”, Proc. of IEEE International Conference on Data Mining (IEEE ICDM), Atlantic City, NJ, 2015 (Regular paper, acceptance rate: 9.5%).

  2. Kotov, M. Hasan, A. Carcone, M. Dong, S. Naar-King and K. Brogan, “Interpretable Probabilistic Latent Variable Models for Automatic Annotation of Clinical Text”, Proc. of American Medical Informatics Association Annual Symposium (AMIA), 2015.

  3. J. Tan, S. Qiao, M. Dong and X. Li, “Using text mining to quantify qualitative data in literature review: A feasibility study”, Health Informatics Information Technology program, APHA Annual Meeting and Exposition, 2015 (abstract).

  4. L. Wang and M. Dong, “Detection of abnormal human behavior using a matrix approximation-based approach”, 13th International Conference on Machine Learning and Applications, Detroit, Michigan, 2014.

  5. R. Almomani, M. Dong and Z. Liu, “Learning Good Features to Track”, 13th International Conference on Machine Learning and Applications, Detroit, Michigan, 2014.

  6. Kotov A, Carcone A, Dong M, Naar-King S, Brogan K, "Towards Automatic Coding of Interview Transcripts for Public Health Research", In Proceedings of the Big Data Analytic Technology For Bioinformatics and Heath Informatics Workshop (KDD-BHI) in conjunction with ACM SIGKDD Conference, 2014.

  7. Z. Huang, M. Dong, Q. Mao, Y. Zhan, “Speech Emotion Recognition using Convolutional Neural Networks”, Proc. of ACM Multimedia (ACM MM), Orlando, Florida, 2014 (poster presentation).

  8. Z. Liu, H. Yang, M. Dong and J. Hua, “A Bayesian Framework for Accurate Eye Center Localization”, Proc. of International Conference of Visual Computing, Las Vegas, Nevada, 2014.

  9. Massuod Alatrash, Hao Ying, Ming Dong and Peter Dews, “A Relevance Feedback-Based System for Biomedical Literature Search”, IEEE Conference on Norbert Wiener in the 21st Century: Driving Technology’s Future (21CW), Boston, MA, 2014.

  10. R. Almomani and M. Dong, “Silhouette-based multi-object tracking with occlusion handling in surveillance videos,” Proc. of International Conference of Image Processing, Melbourne, Australia, 2013.

  11. Massuod Alatrash, Hao Ying, Peter Dews and Ming Dong, “Ranking Biomedical Literature Search Result Based on Relevance Feedback Using Fuzzy Logic and Unified Medical Language System”, Proc. of Annual Meeting of North American Fuzzy Information Processing Society, Berkeley, CA 2012.

  12. Liu, Z. Lai, M. Dong and J. Hua, “Multi-instance Rendering based on Dynamic Differential Surface Propagation”, Proc. of International Conference of Image Processing, Orlando, Florida, 2012.

  13. L. Wang and M. Dong, “Real-time Detection of Abnormal Crowd Behavior Using a Matrix Approximation-based Approach”, Proc. of International Conference of Image Processing, Orlando, Florida, 2012.

  14. L. Wang and M. Dong, “Exemplar-based Low-rank Matrix Decomposition for Data Clustering”, Proc. of International Joint Conference of Neural Networks, 2011.

  15. Massuod Alatrash, Hao Ying, Peter Dews, Ming Dong, Wendy Wu and R.Michael Massanari, “Application of Type-2 Fuzzy Logic to Healthcare Literature Search at Point of Care”, Proc. of Annual Meeting of North American Fuzzy Information Processing Society, 2011.

  16. Y. Chen, M. Dong and W. Wang, "Image Co-clustering with Multi-modality Features and User Feedbacks", Proc. of ACM Multimedia (ACM MM), Beijing, China, 2009.

  17. X. Luo and M. Dong, "Distributed Faulty Sensor Detection in Sensor Networks", Proc. of International Conference on Artificial Neural Networks, Cyprus, 2009.

  18. Y. Chen, L. Wang, and M. Dong, “Semi-supervised Document Clustering with Simultaneous Text Representation and Categorization”, Proc. of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Bled, Slovenia, 2009 (acceptance rate: 22%).

  19. Y. Li, M. Dong and Y. Ma, “Feature Selection for Clustering with Constraints using Jensen-Shannon Divergence”, Proc. of International Conference on Pattern Recognition, Tampa, FL, 2008.

  20. Y. Li, M. Dong and Y. Ma, “Localized Feature Selection for Gaussian Mixtures using Variational Learning”, Proc. of International Conference on Pattern Recognition, Tampa, FL, 2008.

  21. Y. Chen, L. Wang and M. Dong, “A Matrix-based Approach for Semi-supervised Document Co-clustering”, Proc. of ACM 17th Conference on Information and Knowledge Management (ACM CIKM), Napa Valley, CA, 2008 (two page poster).

  22. M. Dong and Y. Chen, "Salient Region Detection and Feature Extraction in Visual Data", Proc. IEEE International Conference on Image Processing, San Diego, 2008.

  23. M. Rege, M. Dong and J. Hua, “Graph Theoretical Framework for Simultaneously Integrating Visual and Textural Features for Efficient Web Image Clustering”, Proc. of 17th International World Wide Web Conference (WWW), 2008, China (regular paper, acceptance rate 11%).

  24. Y. Chen, M. Rege, M. Dong and J. Hua, “Incorporating User provided Constraints into Document Clustering”, Proc. of IEEE International Conference on Data Mining (IEEE ICDM), pp. 103 – 112, Omaha, NE, October 2007 (regular Paper, acceptance rate 7.2%).

  25. Y. Chen, M. Rege, M. Dong and F. Fotouhi, “Deriving Semantics for Image Clustering from Accumulated User Feedbacks”, Proc. of ACM Multimedia (ACM MM), pp. 317 – 320, Germany, 2007 (acceptance rate: 24%).

  26. M. Rege, M. Dong and J. Hua, “Clustering Web Images with Multi-modal Features”, Proc. of ACM Multimedia (ACM MM), pp. 313- 316, Germany, 2007 (acceptance rate: 24%).

  27. Zou, J. Hua, M. Dong, and O. Muzik, “Integrative Information Visualization of Multimodality Neuroimaging Data”, Proc. of the 15th Pacific Graphics Conference, pp 473 – 476, Hawaii, 2007.

  28. Yang, D. Pandian, M. Dong, J. Hua, and E. Mark Haacke, “Automatic Tumor Detection and Recognition in 3D MR Imaging”, In the Annual Joint Molecular Imaging Conference, 2007, (1 page poster).

  29. Y. Li, M. Dong and J. Hua, “Localized Feature Selection for Clustering and its Application in Image Grouping”, Proc. of IEEE International Conference on Multimedia and Expo, pp. 651 – 654, Beijing, China, 2007 (oral presentation, acceptance rate: 16%).

  30. Y. Chen, M. Dong, and M. Rege, “Gene Expression Clustering: A Novel Graph Partitioning Approach”, IEEE International Joint Conference on Neural Networks, pp. 1403 – 1409, Orlando, Florida, August 2007.

  31. Y. Tan, J. Hua, and M. Dong, “3D Reconstruction from 2D Images with Hierarchical Continuous Simplicies”, the 25th Computer Graphics International Conference, Rio de Janeiro, Brazil, June 2007, (Full version is published in the Visual Computer Journal).

  32. Pandian, M. Dong, J. Hua, and E. M. Haacke, “Brain Tumor Detection Using Scale Invariant Feature”, in Annual Meeting of International Society for Magnetic Resonance in Medicine, Germany, 2007, (1 page poster)

  33. Yunhao Tan, Jing Hua, and Ming Dong. Feature Curve-Guided Volume Reconstruction from 2D Images, Proceedings of International Symposium on Biomedical Imaging, pp. 716 – 719, Washington, DC, April 2007.

  34. Darshan Pai, Guangyu Zou, Jing Hua, Ming Dong, Xianfeng Gu, and Otto Muzik. A Conformal and Statistical Surface Mapping Method for 3D PET Image Analysis. Proceedings of the Ninth International Conference on Computer Graphics and Imaging, Austria, February 2007.

  35. M. Rege, M. Dong, and F. Fotouhi, “Co-clustering documents and words using Bipartite Isoperimetric Graph Partitioning, Proc. IEEE International Conference on Data Mining (IEEE ICDM), pp. 532 -541, Hong Kong, China, 2006 (regular paper, acceptance rate: 9.5%).

  36. M. Rege, M. Dong, and F. Fotouhi, “Co-Clustering Image Features and Semantic Concepts”, Proc. IEEE International Conference on Image Processing, pp. 137 - 140, Atlanta, GA, 2006 (acceptance rate: 46%).

  37. M. Dong and J. Wu, “Localized Support Vector Machines Classification”, Proc of IEEE International Joint Conference on Neural Networks, pp. 799 – 805, Vancouver Canada, 2006.

  38. M. Rege, M. Dong, and F. Fotouhi, “Find a semantic structure interactively in image databases”, Proc. of IEEE International Conference on Multimedia and Expo, pp. 81 – 84, Toronto, Canada, 2006 (oral presentation, acceptance rate: 22%).

  39. Yang, M. Dong, and J. Hua, “Region-based Image Annotation using Asymmetrical Support Vector Machine-based Multiple-Instance Learning", Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 2057 – 2063, New York, NY, 2006 (acceptance rate: 19%).

  40. Yang, M. Dong, and F. Fotouhi, “Semantic Feedback to Interactive Image Retrieval", Proc. of ACM International Conference on Multimedia, pp. 415 – 418, Singapore, Nov 6 - 11, 2005 (acceptance rate: 29%).

  41. Yang, M. Dong, and F. Fotouhi, “Region Based Image Annotation Through Multiple-Instance Learning”, Proc. of ACM International Conference on Multimedia, pp 435 – 438, Singapore, Nov 6 - 11, 2005 (acceptance rate: 29%).

  42. X. Luo, M. Dong and Y. Huang, “Optimal Fault-tolerant Event Detection in Wireless Sensor Networks”, Proc. of 13th European Signal Processing Conference, Antalya, Turkey, 2005.

  43. Yang, M. Dong, and F. Fotouhi, “Image content annotation using Bayesian Framework and Complement Components Analysis", Proc. of IEEE International Conference on Image Processing, pp. 1193 – 1196, Genova, Italy, Sept 11 - 14, 2005 (acceptance rate: 46%).

  44. X. Luo, M. Dong, and Y. Huang, “Adaptive Fault-tolerant Event Detection in Sensor Networks”, Proc. of the Second International Workshop on Networked Sensing Systems, pp. 142-147, San Diego, California, 2005.

  45. M. Rege, M. Dong, and F.Fotouhi, “XML Path based Relevance Model for Automatic Image Annotation”, Proc. of IEEE International Conference on Multimedia and Expo, Amsterdam, Netherlands, 2005.

  46. Yang, M. Dong, and F. Fotouhi, “I2A: an Interactive Image Annotation system”, Proc. of IEEE International Conference on Multimedia and Expo, Amsterdam, Netherlands, 2005 (oral presentation, acceptance rate: 22%).

  47. Jing Jiang, Ming Dong, and E. Mark Haacke, “ARGDYP: an adaptive region growing and dynamic programming algorithm for stenosis detection in MRI”, pp. 465 – 468, Proc. of IEEE ICASSP 2005, Philadelphia, PA.

  48. M. Rege, M. Dong, F.Fotouhi, and M. Siadat, “Using MPEG-7 to build a human brain image database for image guided neurosurgery”, Proc. of SPIE International Symposium on Medical Imaging, pp. 5744 – 5756, San Diego, CA, 2005.

  49. Rajeev Agrawal, Farshad Fotouhi, Peter Stanchev, and Ming Dong, “MPEG-7 Based Image Retrieval on the World Wide Web”, Proc. of The Second International Workshop on Multimedia Semantics, pp. 164-175, Sofia, Bulgaria 2004.

  50. Changbo Yang, Ming Dong, and Farshad Fotouhi, “Learning the Semantics in Image Retrieval – A Statistical Natural Language Processing Approach”, Proc. 4th International Workshop on Multimedia Data and Document Engineering, Washington DC, July 2004.

  51. Jing Jiang, Ming Dong and E. Mark Haacke, "A New Method to Measure Cross Sectional Area of Vessels in MRI Image and Its Application in Stenosis Detection", Proc. IEEE International Symposium on Biomedical Imaging, 1043-1046, April, 2004.

  52. William I. Grosky, Farshad Fotouhi, Anthony Aristar, Ming Dong, Hasan Jamil, Shiyong Lu, and Robert Reynolds, “A Digital Library for Endangered Languages”, Proc. of the Symposium for Digital Silk Roads, pp. 85-92, Nara, Japan, December, 2003.

  53. Jeffrey Stefan, Robert Reynolds, Farshad Fotouhi, Anthony Aristar, Shiyong Lu, and Ming Dong, "Evolution Based Approaches to the Preservation of Endangered Natural Languages", Proc. of the IEEE International Congress on Evolutionary Computation, pp.1980-1987, Canberra, Australia, December, 2003.

  54. M. Dong, Y. Li and R. Kothari, "Theoretical Results on A Measure of Classification Complexity", Proc. of 5th International Conference on Advances in Pattern Recognition, pp. 85-88, Calcutta, India, 2003.

  55. X. Duo, M. Dong, F. Fotouhi and L. Schwiebert, "Hierarchical Search and Browsing of Face Image Databases", Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining and Complex Systems, Vol. 13, pp. 601-606, 2003.

  56. Ming Dong and Xu-shen Zhou, "Analyzing Dividend Events with Neural Network Rule Extraction," Proc. International Joint Conference on Neural Networks, pp. 2854- 2859, Portland, OR, 2003.

  57. Y. Li and M. Dong, "Classifiability Based Omnivariate Decision Trees," Proc. International Joint Conference on Neural Networks, pp. 3223-3228, Portland, OR, 2003.

  58. M. Johnson, F. Fotouhi, S. Draghici and M. Dong, "Enhancing Query-by-Structure Neural Network Net Approach ", Proceedings of Workshop on Multimedia Semantics in conjunction with SOFSEM, November 2002.

  59. M. Dong and Xu-shen Zhou, "Analyzing Visual Technical Patterns - A Neural Network Based Saliency Analysis", Proc. International Conference on Neural Information Processing, Vol.5, pp. 2345-2349, Singapore, 2002.

  60. M. Dong and Xu-shen Zhou, "Exploring the Fuzzy Nature of Technical Patterns of U. S Stock Market", Proc. Fuzzy System and Knowledge Discovery, Vol.1, 324-328, 2002, Singapore

  61. M. Dong and R. Kothari, "Classifiability Based Pruning of Decision Trees", Proc. International Joint Conference on Neural Networks, Vol. 3, pp. 1739-1743, 2001.

  62. M. Dong and R. Kothari, "Texture Based Look-Ahead for Decision Tree Induction", International Conference on Advances in Pattern Recognition, Lecture Notes in Computer Science, Vol. 2013, S. Singh, N. Murshed and K. Kropatsch (Eds.), pp. 166-175, Springer-Verlag, 2001.

  63. M. Dong, R. Kothari, M. Visscher and S. Hoath, "Evaluating Skin Condition Using a Decision Tree", Proc. International Joint Conference on Neural Networks, Vol. 4, pp. 2456-2460, 2001.

  64. R. Kothari, M. Dong and D. Bhatia, “Neighborhood Induced Stochastic Resonance”, Proc. IEEE International Joint Conf. on Neural Networks, Vol. 1, pp. 621-624, 1999.

Book Chapters

  1. R. Almomani and M. Dong, “Real Time Objects Tracking with Occlusion Handling in Surveillance Videos”, Robotic Vision: Technologies for Machine Learning and Vision Applications, Chapter 6, pp. 98 - 110, 2012.

  2. M. Rege, M. Dong and F. Fotouhi, “Enhancing e-Business on the Semantic Web through Automatic Multimedia Representation”, Semantic Web Technologies and E-Business, A. F. Salam and J. R. Stevens (Eds.), Chapter VI, pp. 154-168, Idea Group Publishing, 2007.

  3. M. Dong and X. Zhou, “Mining Technical Patterns in U. S. Stock Market through Soft Computing”, Computational Intelligence for Modeling and Predictions, S. Halgamuge and L. Wang (Eds.), Chapter 18, pp. 247-264, Springer-Verlag, 2005.

  4. R. Kothari and M. Dong, “Decision Trees for Classification: A review and some new results”, in Pattern Recognition: From Classical to Modern Approaches, S. R. Pal, and A. Pal (Eds.), Chapter 6, pp. 169-184, World Scientific, 2001.