Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure-Reference-Cited by-同舟云学术

Leveraging Active Learning for Relevance Feedback Using an Information Theoretic Diversity Measure

Published:2006 Issue: Volume: Page:123-132
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Dagli Charlie K.,Rajaram Shyamsundar,Huang Thomas S.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/11788034_13.pdf

Reference14 articles.

1. Rui, Y., Huang, T.S.: Relevance Feedback Techniques in Image Retrieval. In: Lew, M.S. (ed.) Principles of Visual Information Retrieval. Springer, London (2001)

2. Ko, B.C., Byun, H.: Probabilistic Neural Networks Supporting Multi-Class Relevance Feedback in Region-Based Image Retrieval. In: International Conference on Pattern Recognition (2002)

3. Dong, A., Bhanu, B.: Active Concept Learning for Image Retrieval in Dynamic Databases. In: International Conference on Computer Vision (2003)

4. Zhou, X.S., Rui, Y., Huang, T.S.: Exploration of Visual Data. Kluwer Academic Publishers, Dordrecht (2003)

5. Zhou, X., Huang, T.S.: Small Sample Learning during Multimedia Retrieval using BiasMap. In: IEEE Conference Computer Vision and Pattern Recognition (2001)

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