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» Feature selection for content-based image retrieval
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IJCAI
2007
13 years 10 months ago
Logistic Regression Models for a Fast CBIR Method Based on Feature Selection
Distance measures like the Euclidean distance have been the most widely used to measure similarities between feature vectors in the content-based image retrieval (CBIR) systems. H...
Riadh Ksantini, Djemel Ziou, Bernard Colin, Fran&c...
WILF
2009
Springer
196views Fuzzy Logic» more  WILF 2009»
14 years 1 months ago
Interactive Image Retrieval in a Fuzzy Framework
In this paper, an interactive image retrieval scheme using MPEG-7 visual descriptors is proposed. The performance of image retrieval systems is still limited due to semantic gap, w...
Malay Kumar Kundu, Minakshi Banerjee, Priyank Bagr...
PRL
2007
155views more  PRL 2007»
13 years 8 months ago
Integrated patch model: A generative model for image categorization based on feature selection
Image categorization could be treated as an effective solution to enable keyword-based image retrieval. In this paper, we propose a novel image categorization approach by learnin...
Feng Xu, Yu-Jin Zhang
ICIP
2005
IEEE
14 years 2 months ago
Using Tsallis entropy into a Bayesian network for CBIR
This paper presents a Bayesian Network model for ContentBased Image Retrieval (CBIR). In the explanation and test of this work, only two images features (semantic evidences) are i...
Paulo S. Rodrigues, Gilson A. Giraldi, Ade A. Arau...
TKDE
2008
195views more  TKDE 2008»
13 years 8 months ago
Learning a Maximum Margin Subspace for Image Retrieval
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
Xiaofei He, Deng Cai, Jiawei Han