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» Multidimensional Data Modeling for Business Process Analysis
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135
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ECCV
2002
Springer
16 years 5 months ago
Robust Parameterized Component Analysis
Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...
Fernando De la Torre, Michael J. Black
149
Voted
AVSS
2007
IEEE
15 years 10 months ago
Model-based human posture estimation for gesture analysis in an opportunistic fusion smart camera network
In multi-camera networks rich visual data is provided both spatially and temporally. In this paper a method of human posture estimation is described incorporating the concept of a...
Chen Wu, Hamid K. Aghajan
133
Voted
ILP
2007
Springer
15 years 10 months ago
Bias/Variance Analysis for Relational Domains
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Jennifer Neville, David Jensen
148
Voted
ACMICEC
2008
ACM
276views ECommerce» more  ACMICEC 2008»
15 years 5 months ago
A Bayesian network for IT governance performance prediction
The goal of IT governance is not only to achieve internal efficiency in an IT organization, but also to support IT's role as a business enabler. The latter is here denoted IT...
Mårten Simonsson, Robert Lagerström, Po...
139
Voted
ICIP
2000
IEEE
15 years 8 months ago
Modelling Profiles with a Mixture of Gaussians
Point Distribution Models are useful tools for modelling the variability of particular classes of shapes. A common approach is to apply a Principle Component Analysis to the data,...
James Orwell, Darrel Greenhill, Jonathan D. Rymel,...