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VISUAL
1999
Springer
13 years 9 months ago
Relevance Feedback and Term Weighting Schemes for Content-Based Image Retrieval
This paper describes the application of techniques derived from text retrieval research to the content-based querying of image databases. Speci cally, the use of inverted les, fre...
David Squire, Wolfgang Müller 0002, Henning M...
ICIP
2000
IEEE
14 years 6 months ago
Incorporate Support Vector Machines to Content-Based Image Retrieval with Relevant Feedback
By using relevance feedback [6], Content-Based Image Retrieval (CBIR) allows the user to retrieve images interactively. The user can select the most relevant images and provide a ...
Pengyu Hong, Qi Tian, Thomas S. Huang
ICCV
2007
IEEE
14 years 6 months ago
Graph-Cut Transducers for Relevance Feedback in Content Based Image Retrieval
Closing the semantic gap in content based image retrieval (CBIR) basically requires the knowledge of the user's intention which is usually translated into a sequence of quest...
Hichem Sahbi, Jean-Yves Audibert, Renaud Keriven
SPIESR
1998
195views Database» more  SPIESR 1998»
13 years 6 months ago
Relevance Feedback Techniques in Interactive Content-Based Image Retrieval
Content-Based Image Retrieval (CBIR) has become one of the most active research areas in the past few years. Many visual feature representations have been explored and many system...
Yong Rui, Thomas S. Huang, Sharad Mehrotra
ICASSP
2007
IEEE
13 years 11 months ago
Integrating Relevance Feedback in Boosting for Content-Based Image Retrieval
Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...
Jie Yu, Yijuan Lu, Yuning Xu, Nicu Sebe, Qi Tian