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VISUAL
1999
Springer
11 years 4 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...
ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
11 years 4 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang
VIP
2003
11 years 1 months ago
Relevance Feedback for Content-Based Image Retrieval Using Bayesian Network
Relevance feedback is a powerful query modification technique in the field of content-based image retrieval. The key issue in relevance feedback is how to effectively utilize the ...
Jing Xin, Jesse S. Jin
ICIP
2001
IEEE
12 years 1 months ago
A recursive optimal relevance feedback scheme for content based image retrieval
In this paper, an optimal relevance algorithm is proposed, which adapts the response of a content-based image retrieval (CBIR) system to the user's information needs. In part...
Anastasios D. Doulamis, Nikolaos D. Doulamis
ICIP
2000
IEEE
12 years 1 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
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