Region-based image clustering and retrieval using multiple instance learning

Lecture Notes in Computer Science

Volumn 3568, Issue , 2005, Pages 194-204

  Zhang, Chengcui ^a   Chen, Xin ^a  

^a UNIVERSITY OF ALABAMA AT BIRMINGHAM   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GENETIC ALGORITHMS; LEARNING SYSTEMS; PROBLEM SOLVING; SEARCH ENGINES;

IMAGE CLUSTERING; MULTIPLE INSTANCE LEARNING (MIL); SEARCH SPACE; SUPPORT VECTOR MACHINES (SVM);

CONTENT BASED RETRIEVAL;

EID: 26444513210     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/11526346_23     Document Type: Conference Paper

References (10)

1. Schölkopf, B., Platt, J.C. et al: Estimating the Support of a High-dimensional Distribution. Microsoft Research Corporation Technical Report MSR-TR-99-87, 1999.
2. Rui, Y., Huang, T.S., and Mehrotra, S.: Content-based Image Retrieval with Relevance Feedback in MARS. Proc. of the Intl. Conf. on Image Processing, pp. 815-818, 1997.
3. Carson, C., Belongie, S., Greenspan, H., and Malik, J.: Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying. IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 24, No.8, 2002.
4. Su, Z., Zhang, H.J., S. Li, and Ma, S.P.: Relevance Feedback in Content-based Image Retrieval: Bayesian Framework, Feature Subspaces, and Progressing Learning. IEEE Trans. on Image Processing, Vol. 12, No. 8, pp. 924-937, 2003.
5. Maron, O. and Lozano-Perez, T.: A Framework for Multiple Instance Learning. Advances in Natural Information Processing System 10. Cambridge, MA, MIT Press, 1998.
6. Chen, Y., Zhou, X., Tomas, S., and Huang, T.S.: One-Class SVM for Learning in Image Retrieval. Proc. of IEEE International Conf. on Image Processing, 2001.
7. Huang, X., Chen, S.-C., Shyu, M.-L., and Zhang, C.: User Concept Pattern Discovery Using Relevance Feedback and Multiple Instance Learning for Content-Based Image Retrieval. Proc. of the 3rd Intl. Workshop on Multimedia Data Mining (MDM/KDD'2002), pp. 100-108, 2002.
8. Holland, J. H.: Adaptation in Natural and Artificial Systems. University of Michigan Press (1975).
9. Vladimir, E. C. and Murray, A. T.: Spatial Clustering for Data Mining with Genetic Algorithms. Technical Report FTT-TR-97-10, Queensland University of Technology, Faculty of Information Management, September 1997.
10. Gondra, I. and Heisterkamp, D. R.: Adaptive and Efficient Image Retrieval with One-Class Support Vector Machines for Inter-Query Learning. WSEAS Transactions on Circuits and Systems, Vol. 3, No. 2, April 2004, pp. 324-329.