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» Textural Features and Relevance Feedback for Image Retrieval
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CIVR
2007
Springer
280views Image Analysis» more  CIVR 2007»
15 years 6 months ago
Demonstration of image retrieval based on illumination invariant textural MRF features
Content-based image retrieval (CBIR) systems target database images using feature similarities with respect to the query. Our CBIR demonstration utilises novel illumination invari...
Pavel Vacha, Michal Haindl
CIVR
2008
Springer
152views Image Analysis» more  CIVR 2008»
15 years 1 months ago
FISH: a practical system for fast interactive image search in huge databases
The problem of search and retrieval of images using relevance feedback has attracted tremendous attention in recent years from the research community. A real-world-deployable inte...
Pradhee Tandon, Piyush Nigam, Vikram Pudi, C. V. J...
MIR
2004
ACM
171views Multimedia» more  MIR 2004»
15 years 5 months ago
Mean version space: a new active learning method for content-based image retrieval
In content-based image retrieval, relevance feedback has been introduced to narrow the gap between low-level image feature and high-level semantic concept. Furthermore, to speed u...
Jingrui He, Hanghang Tong, Mingjing Li, HongJiang ...
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BMVC
2010
14 years 9 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
2002
IEEE
16 years 1 months ago
Optimal recursive similarity measure estimation for interactive content-based image retrieval
In this paper, a new recursive algorithm is proposed for optimal estimation of similarity measure used in a content-based retrieval system. This is performed through a relevance f...
Anastasios D. Doulamis, Nikolaos D. Doulamis