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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
ICPR
2004
IEEE
14 years 8 months ago
Image Retrieval by Local Evaluation of Nonlinear Kernel Functions around Salient Points
Feature histograms based on the evaluation of Haar integrals with nonlinear kernel functions were used successfully for the purpose of invariant content based image retrieval. In ...
Alaa Halawani, Hans Burkhardt
MIR
2004
ACM
236views Multimedia» more  MIR 2004»
14 years 1 months ago
Boosting contextual information in content-based image retrieval
We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into acc...
Jaume Amores, Nicu Sebe, Petia Radeva, Theo Gevers...
ICIP
2010
IEEE
13 years 5 months ago
Image retrieval with feature selection and relevance feedback
This paper proposes a new content based image retrieval (CBIR) system combined with relevance feedback and the online feature selection procedures. A measure of inconsistency from...
Yu Sun, Bir Bhanu
ICMCS
2000
IEEE
142views Multimedia» more  ICMCS 2000»
14 years 1 days ago
Incorporate Discriminant Analysis with EM Algorithm in Image Retrieval
One of the difficulties of Content-Based Image Retrieval (CBIR) is the gap between high-level concepts and low-level image features, e.g., color and texture. Relevance feedback wa...
Qi Tian, Ying Wu, Thomas S. Huang