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TKDE
2008
195views more  TKDE 2008»
14 years 9 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
ERCIMDL
1997
Springer
169views Education» more  ERCIMDL 1997»
15 years 1 months ago
Relevance Feedback and Query Expansion for Searching the Web: A Model for Searching a Digital Library
: A fully operational large scale digital library is likely to be based on a distributed architecture and because of this it is likely that a number of independent search engines m...
Alan F. Smeaton, Francis Crimmins
CVPR
2008
IEEE
15 years 11 months ago
Semi-supervised SVM batch mode active learning for image retrieval
Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learni...
Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R....
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MIR
2006
ACM
145views Multimedia» more  MIR 2006»
15 years 3 months ago
Similarity learning via dissimilarity space in CBIR
In this paper, we introduce a new approach to learn dissimilarity for interactive search in content based image retrieval. In literature, dissimilarity is often learned via the fe...
Giang P. Nguyen, Marcel Worring, Arnold W. M. Smeu...
ICIP
2001
IEEE
15 years 11 months ago
Performance prediction for vocabulary-supported image retrieval
The majority of today's content based image retrieval systems rely on low-level image descriptors which limit their capability to support meaningful interactions with the use...
Julia Vogel, Bernt Schiele