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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
SIGIR
2009
ACM
16 years 29 days ago
A comparison of retrieval-based hierarchical clustering approaches to person name disambiguation
This paper describes a simple clustering approach to person name disambiguation of retrieved documents. The methods are based on standard IR concepts and do not require any task-s...
Christof Monz, Wouter Weerkamp
ICPR
2008
IEEE
16 years 27 days 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
MICCAI
2005
Springer
15 years 12 months ago
Spectral Clustering Algorithms for Ultrasound Image Segmentation
Abstract. Image segmentation algorithms derived from spectral clustering analysis rely on the eigenvectors of the Laplacian of a weighted graph obtained from the image. The NCut cr...
Neculai Archip, Robert Rohling, Peter Cooperberg, ...
GFKL
2004
Springer
137views Data Mining» more  GFKL 2004»
15 years 11 months ago
Density Estimation and Visualization for Data Containing Clusters of Unknown Structure
Abstract. A method for measuring the density of data sets that contain an unknown number of clusters of unknown sizes is proposed. This method, called Pareto Density Estimation (PD...
Alfred Ultsch