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191
Voted
COOPIS
2004
IEEE
15 years 5 months ago
2004
IEEE
Large scale distributed real time and embedded (DRE) applications are complex entities that are often composed of different subsystems and have stringent Quality of Service (QoS) r...
110
Voted
ICPR
2010
IEEE
15 years 7 months ago
2010
IEEE
Abstract—The classification of sequences requires the combination of information from different time points. In this paper the detection of facial expressions is considered. Exp...
115
Voted
PRIB
2009
Springer
15 years 8 months ago
2009
Springer
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
122
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SSPR
2004
Springer
15 years 7 months ago
2004
Springer
We present a novel clustering method using HMM parameter space and eigenvector decomposition. Unlike the existing methods, our algorithm can cluster both constant and variable leng...
111
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SAC
2008
ACM
15 years 1 months ago
2008
ACM
Ontology learning integrates many complementary techniques, including machine learning, natural language processing, and data mining. Specifically, clustering techniques facilitat...