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» Content-Based Image Retrieval by Relevance Feedback
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ICPR
2000
IEEE
14 years 8 months ago
Feature Relevance Learning with Query Shifting for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai
CVPR
2003
IEEE
14 years 9 months ago
Nearest Neighbor Search for Relevance Feedback
We introduce the problem of repetitive nearest neighbor search in relevance feedback and propose an efficient search scheme for high dimensional feature spaces. Relevance feedback...
Jelena Tesic, B. S. Manjunath
RIAO
2000
13 years 8 months ago
Image indexation and content based search using pre-attentive similarities
We introduce in this paper the general architecture of an image search engine based on pre-attentive similarities. The components of this system are presented and some of them are...
Alexander Heinrichs, Dimitri Koubaroulis, Barbara ...
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 ...
CIVR
2005
Springer
123views Image Analysis» more  CIVR 2005»
14 years 1 months ago
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Chengcui Zhang, Xin Chen