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TKDE
2008
116views more  TKDE 2008»
13 years 7 months ago
Long-Term Cross-Session Relevance Feedback Using Virtual Features
Relevance feedback (RF) is an iterative process, which refines the retrievals by utilizing the user's feedback on previously retrieved results. Traditional RF techniques solel...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...
ICASSP
2007
IEEE
14 years 1 months ago
A Radial Basis Function and Semantic Learning Space Based Composite Learning Approach to Image Retrieval
This paper introduces a composite learning approach for image retrieval with relevance feedback. The proposed system combines the radial basis function (RBF) based lowlevel learni...
Konstantin Shkurko, Xiaojun Qi
MM
2004
ACM
152views Multimedia» more  MM 2004»
14 years 28 days ago
Manifold-ranking based image retrieval
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
Jingrui He, Mingjing Li, HongJiang Zhang, Hanghang...
MM
2009
ACM
187views Multimedia» more  MM 2009»
14 years 5 days ago
Convex experimental design using manifold structure for image retrieval
Content Based Image Retrieval (CBIR) has become one of the most active research areas in computer science. Relevance feedback is often used in CBIR systems to bridge the semantic ...
Lijun Zhang, Chun Chen, Wei Chen, Jiajun Bu, Deng ...
CVPR
2004
IEEE
14 years 9 months ago
Object-Based Image Retrieval Using the Statistical Structure of Images
We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although estimating the object posterior probability density from few examples seems in...
Derek Hoiem, Rahul Sukthankar, Henry Schneiderman,...