Learning pseudo metric for intelligent multimedia data classification and retrieval

Journal of Intelligent Manufacturing

Volumn 16, Issue 6, 2005, Pages 575-586

  Wang, Dianhui ^a   Ma, Xiaohang ^a   Kim, Yong Soo ^b  

^a LA TROBE UNIVERSITY   (Australia)

^b Gachon University   (South Korea)

Author keywords

Images classification and retrieval; Intelligent systems; Learning pseudo metrics; Neural networks

Indexed keywords

DATA PROCESSING; DATABASE SYSTEMS; FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE RETRIEVAL; INTELLIGENT AGENTS; METRIC SYSTEM; MULTIMEDIA SYSTEMS; NEURAL NETWORKS; SEMANTICS;

IMAGES CLASSIFICATION AND RETRIEVAL; INTELLIGENT SYSTEMS; LEARNING PSEUDO METRICS; MULTIMEDIA INFORMATION PROCESSING;

CLASSIFICATION (OF INFORMATION);

EID: 27744600133     PISSN: 09565515     EISSN: 15728145     Source Type: Journal    
DOI: 10.1007/s10845-005-4363-1     Document Type: Article

References (15)

1. Aditya, V., Mario, A. T., Anil, K. J. and Zhang, H. J. (2001) Image classification for content-based indexing. IEEE Transactions On Image Processing, 10, 117-130.
2. Chen, Y. and Wang, J. Z. (2002) A region-based fuzzy feature matching approach to content-based image retrieval. IEEE Transactions On Pattern Analysis and Machine Intelligence, 24, 1252-1267.
3. Crestani, F. and Pasi, G. (ed.), (2000) Soft Computing in Information Retrieval: Techniques and Applications, Physica Verlag (Springer Verlag), Heidelberg, Germany.
4. Dunham, M. H. (2003) Data Mining: Introductory and Advanced Topics, Prentice Hall.
5. Guo, G. D., Jain, A. K., Ma, W. Y. and Zhang, H. J. (2002) Learning similarity measure for natural image retrieval with relevance feedback. IEEE Transactions On Neural Networks, 13, 811-820.
6. He, X. F., King, O., Ma, W. Y., Li, M. J. and Zhang, H. J. (2003) Learning a semantic space from user's relevance feedback for image retrieval. IEEE Transactions On Circuits and Systems for Video Technology, 13, 39-48.
7. Lee, H. K. and Yoo, S. (2001) Intelligent image retrieval using neural network. IEICE Transactions on Information and Systems, 12, 1810-1819.
8. Lim, J. H., Wu, J. K., Singh, S. and Narasimhalu, D. (2001) Learning similarity matching in multimedia content-based retrieval. IEEE Transactions On Knowledge and Data Engineering, 13, 846-850.
9. Munkres, J. R. (2000) Topology, 2nd edn., Prentice-Hall, Upper Saddle River, NJ.
10. Riu, Y., Hunag, T., Ortega, M. and Mehrotra, S. (1998) Relevance feedback: a power tool for interactive content-based image retrieval. IEEE Transactions On Circuit and Systems for Video Technology, 5, 644-656.
11. Rui, Y., Huang, T. S. and Chang, S. F. (1999) Image retrieval: current techniques and promising directions and open issues. Journal of Visual Communication and Image Representation, 10, 39-62.
12. Rumelhart, D. E., Hinton, G. E. and Willianms, R. J. (1986) Learning representations of back-propagation errors, Nature (London), 323, 533-536.
13. Santin, S. and Jain, R. (1999) Similarity measures. IEEE Transactions On Pattern Analysis and Machine Intelligence, 21, 871-883.
14. Wang, D. H., Dillon, T. S. and Ma, X. H. (2003) Robustness for evaluating rule's generalization capability in data mining. Lecture Notes in Computer Science 2903 Springer, 699-709.
15. Yoshitaka, A. and Ichikawa, T. (1999) A survey on content-based retrieval for multimedia databases. IEEE Transactions On Knowledge and Data Engineering, 1-2, 81-93.