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ICASSP
2009
IEEE
16 years 1 months ago
Bandwidth adaptive hardware architecture of K-Means clustering for intelligent video processing
K-Means is a clustering algorithm that is widely applied in many elds, including pattern classi cation and multimedia analysis. Due to real-time requirements and computational-cos...
Tse-Wei Chen, Shao-Yi Chien
ICPR
2008
IEEE
16 years 1 months ago
Kernel Bisecting k-means clustering for SVM training sample reduction
This paper presents a new algorithm named Kernel Bisecting k-means and Sample Removal (KBK-SR) as a sampling preprocessing for SVM training to improve the scalability. The novel c...
Xiao-Zhang Liu, Guo-Can Feng
166
Voted
ISICA
2007
Springer
16 years 24 days ago
Parameter Setting for Evolutionary Latent Class Clustering
The latent class model or multivariate multinomial mixture is a powerful model for clustering discrete data. This model is expected to be useful to represent non-homogeneous popula...
Damien Tessier, Marc Schoenauer, Christophe Bierna...
AAIM
2007
Springer
118views Algorithms» more  AAIM 2007»
15 years 10 months ago
Significance-Driven Graph Clustering
Abstract. Modularity, the recently defined quality measure for clusterings, has attained instant popularity in the fields of social and natural sciences. We revisit the rationale b...
Marco Gaertler, Robert Görke, Dorothea Wagner
ESANN
2000
15 years 8 months ago
Automatic detection of clustered microcalcifications in digital mammograms using an SVM classifier
In this paper we investigate the performance of a Computer Aided Diagnosis (CAD) system for the detection of clustered microcalcifications in mammograms. Our detection algorithm co...
Armando Bazzani, Alessandro Bevilacqua, Dante Boll...