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» A two-level relevance feedback mechanism for image retrieval
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CIVR
2008
Springer
127views Image Analysis» more  CIVR 2008»
14 years 11 months ago
Performance evaluation of relevance feedback methods
In this paper we review the evaluation of relevance feedback methods for content-based image retrieval systems. We start out by presenting an overview of current common practice, ...
Mark J. Huiskes, Michael S. Lew
101
Voted
ICMCS
2000
IEEE
142views Multimedia» more  ICMCS 2000»
15 years 2 months 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
88
Voted
BMVC
2010
14 years 7 months ago
Trans Media Relevance Feedback for Image Autoannotation
Automatic image annotation is an important tool for keyword-based image retrieval, providing a textual index for non-annotated images. Many image auto annotation methods are based...
Thomas Mensink, Jakob J. Verbeek, Gabriela Csurka
ICIP
2001
IEEE
15 years 11 months ago
VISMap: an interactive image/video retrieval system using visualization and concept maps
Images and videos can be indexed by multiple features at different levels, such as color, texture, motion, and text annotation. Organizing this information into a system so that u...
William Chen, Shih-Fu Chang
74
Voted
PRIS
2001
14 years 11 months ago
Relevance Feedback in Content-based Image Search
: Content-based image retrieval (CBIR) is a research area dedicated to address the retrieve and search multimedia documents for digital libraries. Relevance feedback is a powerful ...
HongJiang Zhang