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» Adaptable Similarity Search Using Vector Quantization
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ICIP
2007
IEEE
13 years 12 months ago
Adaptive Cluster-Distance Bounding for Nearest Neighbor Search in Image Databases
We consider approaches for exact similarity search in a high dimensional space of correlated features representing image datasets, based on principles of clustering and vector qua...
Sharadh Ramaswamy, Kenneth Rose
WSOM
2009
Springer
14 years 4 days ago
Incremental Figure-Ground Segmentation Using Localized Adaptive Metrics in LVQ
Vector quantization methods are confronted with a model selection problem, namely the number of prototypical feature representatives to model each class. In this paper we present a...
Alexander Denecke, Heiko Wersing, Jochen J. Steil,...
IVC
2007
94views more  IVC 2007»
13 years 5 months ago
Vector quantization and fuzzy ranks for image reconstruction
The problem of clustering is often addressed with techniques based on a Voronoi partition of the data space. Vector quantization is based on a similar principle, but it is a diffe...
Stefano Rovetta, Francesco Masulli
ESANN
1997
13 years 7 months ago
Kohonen maps versus vector quantization for data analysis
Besides their topological properties, Kohonen maps are often used for vector quantization only. These auto-organised networks are often compared to other standard and/or adaptive v...
Eric de Bodt, Michel Verleysen, Marie Cottrell
VLDB
2002
ACM
138views Database» more  VLDB 2002»
13 years 5 months ago
Adaptable Similarity Search using Non-Relevant Information
Many modern database applications require content-based similarity search capability in numeric attribute space. Further, users' notion of similarity varies between search se...
T. V. Ashwin, Rahul Gupta, Sugata Ghosal