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Le Dong

Le Dong

Contact Details

Title: Research Student
Tel: National: 020 7882 5352
International: +44 20 7882 5352
Fax: National: 020 7882 7997
International: +44 20 7882 7997
Room: 153
Email:

Research Group: Multimedia and Vision Research Group

Supervisor: Prof Ebroul Izquierdo

Research Topic: A Biologically Inspired System for Classification of Visual Information

Research interests

Biologically Inspired System
Computer Vision, Visual Recognition/Perception
Statistical Learning and Pattern Classification
Vision-based Interaction, Image/Video Analysis and Understanding
Multimedia Processing and Knowledge Representation

Participation in projects:

MESH

Biography

Le Dong received the B.E. degree in telecommunication engineering and the M.E. degree in communications and information systems from Xidian University, Xi'an, China, in 2001 and 2004, respectively. She is currently working toward the Ph.D. degree with the Multimedia and Vision Group, Department of Electronic Engineering, Queen Mary, University of London, London, U.K.
Her research interests are in biologically inspired systems, image processing, pattern classification, and knowledge representation.

Publications:

Journals

  • L. Dong and E. Izquierdo, "A Biologically Inspired Dynamic Network Structure for Clustering of Visual Information," IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, iss. 5, pp. 590–603, 2007.
  • L. Dong and E. Izquierdo, "A Knowledge Synthesizing Approach for Classification of Visual Information," LNCS, vol. 4781, pp. 17–25, 2007.
  • L. Dong, S. W. Ban, I. Lee, and M. Lee, "Incremental Knowledge Representation Model Based on Visual Selective Attention," Neural Information Processing - Letters and Reviews, vol. 10, iss. 4-6, pp. 115–124, 2006.
  • L. Dong, S. W. Ban, and M. Lee, "Biologically Inspired Selective Attention Model Using Human Interest," International Journal of Information Technology, vol. 12, iss. 2, pp. 140–148, 2006.

Conferences

  • L. Dong and E. Izquierdo, "A Knowledge Structuring Technique for Image Classification," in Proc. International Conference on Image Processing, 2007, pp. 377–380.
  • L. Dong and E. Izquierdo, "A Biologically Inspired Knowledge Structuring Technique for Classification of Visual Information," in Proc. 9th International Conference on Visual Information Systems, 2007,
  • L. Dong and E. Izquierdo, "A Topology Preserving Approach for Image Classification," in Proc. 8th International Workshop on Image Analysis for Multimedia Interactive Services, 2007,
  • L. Dong and E. Izquierdo, "Global-to-Local Motivated Scene Recognition," in Proc. First Doctoral Symposium on Computing, 2007, pp. 37–44.
  • L. Dong, S. W. Ban, and M. Lee, "An Incremental Self-organizing Network for Knowledge Inference and Topology Representation," in Proc. 2nd Joint Symposium for Computational Intelligence, 2006, pp. 44–47.
  • L. Dong, S. W. Ban, and M. Lee, "Biologically Inspired Selective Attention Model Using Human Interest," in Proc. International Conference on Intelligent Computing, 2005, pp. 480–489.
  • L. Dong, S. W. Ban, and M. Lee, "Knowledge Representation Model Based on Visual Selective Attention for Autonomous Mental Development," in Proc. IJCNN Workshop on Biologically-Inspired Models and Hardware for Human-like Intelligent Functions, 2005, pp. 6–10.
  • L. Dong, S. W. Ban, and M. Lee, "Biologically Motivated Knowledge Representation Based on Selective Attention Model with Preference Reflection," in Proc. Conference on Brain Science, 2005, pp. 124–124.
  • L. Dong, S. W. Ban, and M. Lee, "Modified Bottom-up Saliency Map Model Based on Human Interaction," in Proc. 1st Joint Symposium for Computational Intelligence, 2005, pp. 153–154.
  • L. Dong and H. L. Zhang, "Multi-User MIMO-OFDM System and Its Enhanced Channel Estimation Algorithm," in Proc. Graduate Academic Conference of Xidian University, 2003, pp. 258–264.
  • L. Dong and H. L. Zhang, "An Enhanced Channel Estimation Algorithm for MIMO-OFDM System," in Proc. Academic Annual Conference on China Communication Academy Wireless and Mobile Communication Committee, 2003, pp. 446–451.
 
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Electronic Engineering, Queen Mary University of London, Mile End Road, London E1 4NS, UK Tel: +44 (0)20 7882 5346, Fax: +44 (0)20 7882 7997