Abstract
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on One-Class Support Vector Machine (SVM) to solve MIL problem in the region-based Content Based Image Retrieval (CBIR). Relevance Feedback technique is incorporated to provide progressive guidance to the learning process. Performance is evaluated and the effectiveness of our retrieval algorithm has been shown through comparative studies.
| Original language | English (US) |
|---|---|
| Title of host publication | IEEE International Conference on Multimedia and Expo, ICME 2005 |
| Pages | 1142-1145 |
| Number of pages | 4 |
| DOIs | |
| State | Published - Dec 1 2005 |
| Event | IEEE International Conference on Multimedia and Expo, ICME 2005 - Amsterdam, Netherlands Duration: Jul 6 2005 → Jul 8 2005 |
Publication series
| Name | IEEE International Conference on Multimedia and Expo, ICME 2005 |
|---|---|
| Volume | 2005 |
Other
| Other | IEEE International Conference on Multimedia and Expo, ICME 2005 |
|---|---|
| Country | Netherlands |
| City | Amsterdam |
| Period | 7/6/05 → 7/8/05 |
ASJC Scopus subject areas
- Engineering(all)
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Cite this
Zhang, C., Chen, X., Chen, M., Chen, S. C., & Shyu, M. L. (2005). A multiple instance learning approach for content based image retrieval using one-class support vector machine. In IEEE International Conference on Multimedia and Expo, ICME 2005 (pp. 1142-1145). [1521628] (IEEE International Conference on Multimedia and Expo, ICME 2005; Vol. 2005). https://doi.org/10.1109/ICME.2005.1521628