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VISUAL
1999
Springer
11 years 2 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 2 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
10 years 11 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
11 years 11 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
11 years 11 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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