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» Kernel indexing for relevance feedback image retrieval
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ICDE
2006
IEEE
191views Database» more  ICDE 2006»
14 years 8 months ago
Query Decomposition: A Multiple Neighborhood Approach to Relevance Feedback Processing in Content-based Image Retrieval
Today's Content-Based Image Retrieval (CBIR) techniques are based on the "k-nearest neighbors" (kNN) model. They retrieve images from a single neighborhood using lo...
Kien A. Hua, Ning Yu, Danzhou Liu
ICIP
2001
IEEE
14 years 9 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
CBMS
2005
IEEE
14 years 1 months ago
Relevance Feedback for Spine X-ray Retrieval
Relevance feedback (RF) has been an active research area in Content-based Image Retrieval (CBIR). RF intends to bridge the gap between the low-level image features and the high-le...
Xiaoqian Xu, D. J. Lee, Sameer Antani, L. Rodney L...
SAC
2006
ACM
14 years 1 months ago
Relevance feedback methods for logo and trademark image retrieval on the web
Relevance feedback is the state-of-the-art approach for adjusting query results to the needs of the users. This work extends the existing framework of image retrieval with relevan...
Euripides G. M. Petrakis, Klaydios Kontis, Epimeni...
MTA
2002
166views more  MTA 2002»
13 years 7 months ago
MUSE: A Content-Based Image Search and Retrieval System Using Relevance Feedback
ThefieldofContent-BasedVisualInformationRetrieval(CBVIR)hasexperiencedtremendousgrowth in the recent years and many research groups are currently working on solutions to the proble...
Oge Marques, Borko Furht