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» Learning an image manifold for retrieval
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ICMCS
2005
IEEE
221views Multimedia» more  ICMCS 2005»
14 years 2 months ago
A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
ICCV
2003
IEEE
14 years 2 months ago
Active Concept Learning for Image Retrieval in Dynamic Databases
Concept learning in content-based image retrieval (CBIR) systems is a challenging task. This paper presents an active concept learning approach based on mixture model to deal with...
Anlei Dong, Bir Bhanu
ECCV
2000
Springer
14 years 10 months ago
Learning Over Multiple Temporal Scales in Image Databases
Abstract. The ability to learn from user interaction is an important asset for content-based image retrieval (CBIR) systems. Over short times scales, it enables the integration of ...
Nuno Vasconcelos, Andrew Lippman
DAGM
2006
Springer
14 years 15 days ago
Parameterless Isomap with Adaptive Neighborhood Selection
Abstract. Isomap is a highly popular manifold learning and dimensionality reduction technique that effectively performs multidimensional scaling on estimates of geodesic distances....
Nathan Mekuz, John K. Tsotsos
SIGIR
2008
ACM
13 years 8 months ago
Learning to reduce the semantic gap in web image retrieval and annotation
We study in this paper the problem of bridging the semantic gap between low-level image features and high-level semantic concepts, which is the key hindrance in content-based imag...
Changhu Wang, Lei Zhang 0001, Hong-Jiang Zhang