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MTA
2008
146views more  MTA 2008»
13 years 10 months ago
A survey of browsing models for content based image retrieval
The problem of content based image retrieval (CBIR) has traditionally been investigated within a framework that emphasises the explicit formulation of a query: users initiate an au...
Daniel Heesch
ESWA
2008
127views more  ESWA 2008»
13 years 10 months ago
A two-level relevance feedback mechanism for image retrieval
Content-based image retrieval (CBIR) is a group of techniques that analyzes the visual features (such as color, shape, texture) of an example image or image subregion to find simi...
Pei-Cheng Cheng, Been-Chian Chien, Hao-Ren Ke, Wei...
ICIP
2003
IEEE
14 years 11 months ago
Performance evaluation of Euclidean/correlation-based relevance feedback algorithms in content-based image retrieval systems
In this paper, we evaluate and investigate two main types of relevance feedback algorithms; the Euclidean and the correlation?based approaches. In the first case, we examine heuri...
Anastasios D. Doulamis, Nikolaos D. Doulamis
MIR
2006
ACM
145views Multimedia» more  MIR 2006»
14 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
2003
IEEE
14 years 11 months ago
Kernel indexing for relevance feedback image retrieval
Relevance feedback is an attractive approach to developing flexible metrics for content-based retrieval in image and video databases. Large image databases require an index struct...
Jing Peng, Douglas R. Heisterkamp