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ESWA
2008
116views more  ESWA 2008»
15 years 4 months ago
The application of clustering analysis for the critical areas on TFT-LCD panel
For thin film transistor-liquid crystal displays (TFT-LCD) factories in Taiwan, yield performance had become as an important competitiveness determinant during the competitive env...
Kun-Lin Hsieh
CSDA
2006
91views more  CSDA 2006»
15 years 4 months ago
Model-based cluster and discriminant analysis with the MIXMOD software
The mixmod (mixture modeling) program fits mixture models to a given data set for the purposes of density estimation, clustering or discriminant analysis. A large variety of algor...
Christophe Biernacki, Gilles Celeux, Gérard...
ICDAR
2009
IEEE
15 years 2 months ago
Analysis of Book Documents' Table of Content Based on Clustering
Table of contents (TOC) recognition has attracted a great deal of attention in recent years. After reviewing the merits and drawbacks of the existing TOC recognition methods, we h...
Liangcai Gao, Zhi Tang, Xiaofan Lin, Xin Tao, Yimi...
EVOW
2010
Springer
15 years 11 months ago
Towards Automatic Detecting of Overlapping Genes - Clustered BLAST Analysis of Viral Genomes
Overlapping genes (encoded on the same DNA strand but in different frames) are thought to be rare and, therefore, were largely neglected in the past. In a test set of 800 viruses ...
Klaus Neuhaus, Daniela Oelke, David Fürst, Si...
ISAAC
2009
Springer
175views Algorithms» more  ISAAC 2009»
15 years 11 months ago
Worst-Case and Smoothed Analysis of k-Means Clustering with Bregman Divergences
The k-means algorithm is the method of choice for clustering large-scale data sets and it performs exceedingly well in practice. Most of the theoretical work is restricted to the c...
Bodo Manthey, Heiko Röglin