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» Optimizing Learning in Image Retrieval
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CLEF
2007
Springer
14 years 1 months ago
Speeding Up IDM without Degradation of Retrieval Quality
The Image Distortion Model (IDM) has shown good retrieval quality in previous runs of the medical automatic annotation task of previous ImageCLEF workshops. However, one of its li...
Michael Springmann, Heiko Schuldt
MTA
2006
169views more  MTA 2006»
13 years 7 months ago
MBC-based shape retrieval: basics, optimizations, and open problems
Shape of an object is an important feature for image and multimedia similarity retrievals. In our previous studies we introduced a new boundary-based technique (MBC-based) for shap...
Maytham Safar, Cyrus Shahabi
MLDM
1999
Springer
13 years 12 months ago
Non-hierarchical Clustering with Rival Penalized Competitive Learning for Information Retrieval
In large content-based image database applications, e cient information retrieval depends heavily on good indexing structures of the extracted features. While indexing techniques f...
Irwin King, Tak-Kan Lau
CIVR
2006
Springer
145views Image Analysis» more  CIVR 2006»
13 years 11 months ago
Learned Lexicon-Driven Interactive Video Retrieval
Abstract. We combine in this paper automatic learning of a large lexicon of semantic concepts with traditional video retrieval methods into a novel approach to narrow the semantic ...
Cees Snoek, Marcel Worring, Dennis Koelma, Arnold ...
NIPS
2004
13 years 9 months ago
Instance-Based Relevance Feedback for Image Retrieval
High retrieval precision in content-based image retrieval can be attained by adopting relevance feedback mechanisms. These mechanisms require that the user judges the quality of t...
Giorgio Giacinto, Fabio Roli