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ICMCS
2005
IEEE
221views Multimedia» more  ICMCS 2005»
14 years 1 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...
JDCTA
2010
170views more  JDCTA 2010»
13 years 2 months ago
Color and Texture Feature For Content Based Image Retrieval
Content based image retrieval (CBIR) has been one of the most important research areas in computer science for the last decade. A retrieval method which combines color and texture...
Jianhua Wu, Zhaorong Wei, Youli Chang
MLDM
2001
Springer
13 years 12 months ago
Adaptive Query Shifting for Content-Based Image Retrieval
: Despite the efforts to reduce the semantic gap between user perception of similarity and featurebased representation of images, user interaction is essential to improve retrieval...
Giorgio Giacinto, Fabio Roli, Giorgio Fumera
CVPR
2008
IEEE
14 years 9 months ago
Private Content Based Image Retrieval
For content level access, very often database needs the query as a sample image. However, the image may contain private information and hence the user does not wish to reveal the ...
Jagarlamudi Shashank, Palivela Kowshik, Kannan Sri...
ICPR
2002
IEEE
14 years 8 months ago
Content Based Image Retrieval Using Optimum Peano Scan
We present a new technique for content based image retrieval where feature vector to be matched is very much specific to the query image. A particular Peano scan which is optimal ...
N. Jhanwar, Subhasis Chaudhuri, Guna Seetharaman, ...