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CVPR
2008
IEEE
14 years 9 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
SISAP
2008
IEEE
147views Data Mining» more  SISAP 2008»
14 years 2 months ago
An Empirical Evaluation of a Distributed Clustering-Based Index for Metric Space Databases
Similarity search has been proved suitable for searching in very large collections of unstructured data objects. We are interested in efficient parallel query processing under si...
Veronica Gil Costa, Mauricio Marín, Nora Re...
CGF
2010
171views more  CGF 2010»
13 years 4 months ago
Efficient Mean-shift Clustering Using Gaussian KD-Tree
Mean shift is a popular approach for data clustering, however, the high computational complexity of the mean shift procedure limits its practical applications in high dimensional ...
Chunxia Xiao, Meng Liu
ICDM
2003
IEEE
138views Data Mining» more  ICDM 2003»
14 years 1 months ago
Ontologies Improve Text Document Clustering
Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large sets of documents into a small number of meaningful ...
Andreas Hotho, Steffen Staab, Gerd Stumme
ICIP
2009
IEEE
14 years 8 months ago
Unsupervised Seabed Segmentation Of Synthetic Aperture Sonar Imagery Via Wavelet Features And Spectral Clustering
An unsupervised seabed segmentation algorithm for synthetic aperture sonar (SAS) imagery is proposed. Each 2 m ? 2 m area of seabed is treated as a unique data point. A set of fea...