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» Using Linguistic Models for Image Retrieval
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ICPR
2008
IEEE
14 years 8 months ago
Visual features with semantic combination using Bayesian network for a more effective image retrieval
In many vision problems, instead of having fully annotated training data, it is easier to obtain just a subset of data with annotations, because it is less restrictive for the use...
Sabine Barrat, Salvatore Tabbone
KES
2004
Springer
14 years 1 months ago
Content-Based Image Retrieval Using Multiple Representations
Many different approaches for content-based image retrieval have been proposed in the literature. Successful approaches consider not only simple features like color, but also take ...
Karin Kailing, Hans-Peter Kriegel, Stefan Schö...
CIVR
2007
Springer
104views Image Analysis» more  CIVR 2007»
14 years 1 months ago
Semantic facets: an in-depth analysis of a semantic image retrieval system
This paper introduces a faceted model of image semantics which attempts to express the richness of semantic content interpretable within an image. Using a large image data-set fro...
Jonathon S. Hare, Paul H. Lewis, Peter G. B. Enser...
WACV
2002
IEEE
14 years 16 days ago
Retrieving Faces by the PIFS Fractal Code
The use of fractals in computer graphics and vision in modeling unstructured images, and compressing images, is well known. However, the use of fractals for indexing images in con...
Sharat Chandran, Soumitra Kar
VIP
2003
13 years 9 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