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» Large Model Visualization: Techniques and Applications
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CVPR
2008
IEEE
15 years 2 days ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
NC
2006
132views Neural Networks» more  NC 2006»
13 years 10 months ago
Learning short multivariate time series models through evolutionary and sparse matrix computation
Multivariate Time Series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is...
Stephen Swift, Joost N. Kok, Xiaohui Liu
OOPSLA
2005
Springer
14 years 3 months ago
Using dependency models to manage complex software architecture
An approach to managing the architecture of large software systems is presented. Dependencies are extracted from the code by a conventional static analysis, and shown in a tabular...
Neeraj Sangal, Ev Jordan, Vineet Sinha, Daniel Jac...
MIR
2005
ACM
133views Multimedia» more  MIR 2005»
14 years 3 months ago
Probabilistic web image gathering
We propose a new method for automated large scale gathering of Web images relevant to specified concepts. Our main goal is to build a knowledge base associated with as many conce...
Keiji Yanai, Kobus Barnard
PG
2003
IEEE
14 years 3 months ago
Hierarchical Least Squares Conformal Map
A texture atlas is an efficient way to represent information (like colors, normals, displacement maps ...) on triangulated surfaces. The LSCM method (Least Squares Conformal Maps...
Nicolas Ray, Bruno Lévy