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» User Adaptive Clustering for Large Image Databases
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ICPR
2010
IEEE
13 years 2 months ago
User Adaptive Clustering for Large Image Databases
Abstract--Searching large image databases is a time consuming process when done manually. Current CBIR methods mostly rely on training data in specific domains. When source and dom...
Mohammad Mehdi Saboorian, Mansour Jamzad, Hamid R....
SPIESR
2004
117views Database» more  SPIESR 2004»
13 years 6 months ago
Image database clustering with SVM-based class personalization
To allow efficient browsing of large image collections, we have to provide a summary of its visual content. We present in this paper a robust approach to organize image databases:...
Bertrand Le Saux, Nozha Boujemaa
VLDB
1997
ACM
141views Database» more  VLDB 1997»
13 years 8 months ago
Efficient User-Adaptable Similarity Search in Large Multimedia Databases
Efficient user-adaptable similarity search more and more increases in its importance for multimedia and spatial database systems. As a general similarity model for multi-dimension...
Thomas Seidl, Hans-Peter Kriegel
SIGMOD
2003
ACM
237views Database» more  SIGMOD 2003»
14 years 4 months ago
Qcluster: Relevance Feedback Using Adaptive Clustering for Content-Based Image Retrieval
The learning-enhanced relevance feedback has been one of the most active research areas in content-based image retrieval in recent years. However, few methods using the relevance ...
Deok-Hwan Kim, Chin-Wan Chung
CVDB
2005
ACM
13 years 6 months ago
Optimizing progressive query-by-example over pre-clustered large image databases
The typical mode for querying in an image content-based information system is query-by-example, which allows the user to provide an image as a query and to search for similar imag...
Anicet Kouomou Choupo, Laure Berti-Equille, Annie ...