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黄厚生博士 Dr. Raymond Hau San WONG

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黄厚生, 副教授,现任香港城市大学多媒体软件工程研究中心研究员。他在香港中文大学取得电子工程学士及硕士学位,并在澳大利亚悉尼大学取得电气与信息工程博士学位。 加入香港城市大学之前,他在悉尼大学电气与信息工程学院担任研究助理,并在香港浸会大学担任博士后教学工作。


代表出版物(Representative Publications)

  • ·Z. Yu, H.S. Wong, D. Wang and M. Wei, "Neighborhood Knowledge-Based Evolutionary Algorithm for Multiobjective Optimization Problems", IEEE Trans. on Evolutionary Computation, vol. 15, no. 6, pp. 812-831, 2011.
  • ·Y. Shen, H.S. Wong, S. Zhang and Z. Yu, "Feature-Based 3D Motif Filtering for Ribosomal RNA", Bioinformatics, vol. 27, iss. 20, 2011.
  • ·Y. Shen, S. Zhang, H.S. Wong and L. Zhang, "Characterization of semantic similarity on Gene Ontology based on a shortest path approach", accepted by International Journal of Data Mining and Bioinformatics, 2011.
  • ·S. Zhang, H.S. Wong, Z. Yu and H.H.S. Ip, "Hybrid Associative Retrieval of Three-Dimensional Models", IEEE Trans. on Systems, Man and Cybernetics-Part B: Cybernetics, vol. 40, no. 6, pp. 1582-1595, 2010.
  • ·Z. Yu and H.S. Wong, "Quantization-Based Clustering Algorithm", Pattern Recognition, vol.43, iss. 8, pp. 2698-2711, 2010.
  • ·Z. Yu, H.S. Wong, H. Peng and Q. Ma, "ASM: An Adaptive Simplification Method for 3D Point-Based Models", Computer-Aided Design, vol. 42, iss. 7, pp. 598-612, 2010.
  • ·Z. Yu, Z. Deng, H.S. Wong and L. Tan, "Identifying Protein Kinase-Specific Phosphorylation Sites based on the Bagging-AdaBoost Ensemble Approach ", IEEE Trans. on Nanobioscience, vol. 9, no. 2, pp. 132-143, 2010.
  • ·H. Wang, H.S. Wong, H. Zhu and T. Yip, "A Neural Network-Based Biomarker Association Information Extraction Approach for Cancer Classification", Journal of Biomedical Informatics, vol. 42, iss. 4, pp. 654-666, 2009.
  • ·H.S. Wong and H. Wang, "Constructing the Gene Regulation Level Representation of Microarray Data for Cancer Classification", Journal of Biomedical Informatics , vol. 41, iss. 1, 2008.
  • ·H.S. Wong, B. Ma, Y. Sha and H.H.S. Ip, "3D Head Model Retrieval in Kernel Feature Space Using HSOM", Pattern Recognition , vol. 41, iss. 2, 2008.
  • ·Z. Yu, H.S. Wong and H. Wang, "Graph-based Consensus Clustering for Class Discovery from Gene Expression Data", Bioinformatics , vol. 23, no. 21, pp. 2888-2896, 2007.
  • ·H. Wang, H.S. Wong, D. Huang and J. Shu, "Extracting Gene Regulation Information for Cancer Classification", Pattern Recognition , vol. 40, iss. 12, 2007.
  • ·H. S. Wong, B. Ma, Z. Yu, P.F. Yeung and H.H.S. Ip, "3D Head Model Retrieval Using a Single Face View Query", IEEE Trans. on Multimedia , vol 9, no 5, pp. 1026-1036, 2007.
  • ·Z. Yu and H.S. Wong, "A Rule Based Technique for Extraction of Visual Attention Regions Based on Real-Time Clustering", IEEE Trans. on Multimedia , vol 9, no 4, pp. 766-784, 2007.
  • ·P. Chen, B. Wang, H.S. Wong and D Huang, "Prediction of Protein B-factors Using Multi-Class Bounded SVM", Protein and Peptide Letters , vol 14, iss.2, pp. 185-190, 2007.
  • ·B. Wang, H.S. Wong and D. Huang, "Inferring Protein-Protein Interaction Sites Using Residue Conservation and Evolutionary Information ", Protein and Peptide Letters , vol 13, iss. 10, pp. 999-1005, 2006.
  • ·X.Y. Jing, H.S. Wong and D. Zhang, "Face Recognition Based on 2D Fisherface Approach", Pattern Recognition , vol. 39, issue 4, pp. 707-710, 2006.
  • ·B. Ma and H.S. Wong, "2D Clustering Based Discriminant Analysis for 3D Head Model Classification", Pattern Recognition , vol. 39, issue 3, pp. 491-494, 2006.
  • ·H.S. Wong, K.T.K. Cheung, C.I. Chiu and H.S.H. Ip, "Application of Evolutionary Strategies for 3D Graphical Model Categorization and Retrieval", Multimedia Systems , vol. 10, no.5, pp. 422-431, 2005.
  • ·H.S. Wong, K.T.K. Cheung and H.S.H. Ip, "3D Head Model Classification by Evolutionary Optimization of the Extended Gaussian Image Representation", Pattern Recognition , vol. 37, pp. 2307-2322, 2004.
  • ·H. S. Wong and R. Chung, "3-D Shape Recovery across Two Views Using Approximate Geometric Constraints ", Optical Engineering, vol 42, no. 3, pp. 632-641, 2003.
  • ·R. Chung and H. S. Wong, "Polyhedral Localization in an Image by Referencing to a Single Model View ", International Journal of Computer Vision, vol 51, no. 2, pp. 139-163, 2003.