
[1] Y. Song, W. Wang, and A. Zhang, "Analyzing Scenery Images by Monotonic Tree", ACM/Springer Multimedia Systems Journal, p. 495, vol.
8, (2003).
[2] Y. Song, W. Wang, and A. Zhang, "Automatic Annotation and Retrieval of Images", the World Wide Web (WWW) Journal, p. 209, vol. 6,
(2003).
[3] Y. Shi, Y. Song and A. Zhang, "A Shrinking-Based Clustering Approach for Multi-Dimensional Data", IEEE Transactions on Knowledge and
Data Engineering, accepted.
[4] Y. Wu and A. Zhang, "Interactive Pattern Analysis for Relevance Feedback", ACM/Springer Multimedia Systems Journal, p. 41, vol. 10,
(2004).
[5] A. Zhang, Y. Song, and R. Aygun, "Feature-based Retrieval in Visual Database Systems", book chapter,
Editor(s): D. Feng, W. C. Siu and H.J. Zhang
Collection: Multimedia Information Retrieval and Management,
Springer, pp. 226-245, 2003.
[6] Y. Wu and A. Zhang, "An Adaptive Classification Method for Multimedia Retrieval", proceedings of the 2003 IEEE International Conference on Multimedia and Expo (ICME),
Baltimore, MD, July 6-9.
[7] W. Wang, Y. Song, and A. Zhang, "Identification of Objects from Image Regions," proceedings of
2003 IEEE International Conference on Multimedia and Expo
(ICME), Baltimore, MD, July 6-9.
[8] Y. Wu and A. Zhang,
"Adaptive Pattern Discovery for Interactive Multimedia Retrieval", proceedings of
IEEE Conference on Computer Vision and Pattern Recognition
(CVPR), Madison, Wisconsin, June 16-22.
[9] Y. Wu and A. Zhang,
"Feature Selection for Classifying High-Dimensional
Numerical Data", proceedings of
IEEE Computer Society Conference on Computer Vision and Pattern Recognition
(CVPR04), Washington, DC, 27th June - 2nd July, 2004.
[10] Y. Shi, Y. Song
and A. Zhang, "A Shrinking-Based Approach for Multi-Dimensional Data Analysis", proceedings of
the 29th International Conference on Very Large Data Bases (VLDB03),
Berlin, Germany, September 9-12, 2003.
[11] D. Ma and A. Zhang,
"An Adaptive Density-Based Clustering Algorithm for Spatial Database with Noise", Proceedings of
The Fourth IEEE International Conference on Data Mining (ICDM2004)
Brighton, UK, November 01 - 04.