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CORR
2010
Springer
67views Education» more  CORR 2010»
15 years 7 months ago
From granular avalanches to fluid turbulences through oozing pastes. A mesoscopic physically-based particle model
In this paper, we describe how we can precisely produce complex and various dynamic morphological features such as structured and chaotic features which occur in sand pilings (pil...
Annie Luciani
MVA
2002
195views Computer Vision» more  MVA 2002»
15 years 6 months ago
Improved Adaptive Mixture Learning for Robust Video Background Modeling
2 Related Works Gaussian mixtures are often used for data modeling in many real-time applications such as video background modeling and speaker direction tracking. The real-time a...
Dar-Shyang Lee
DAC
2007
ACM
16 years 8 months ago
GlitchMap: An FPGA Technology Mapper for Low Power Considering Glitches
In 90-nm technology, dynamic power is still the largest power source in FPGAs [1], and signal glitches contribute a large portion of the dynamic power consumption. Previous powera...
Lei Cheng, Deming Chen, Martin D. F. Wong
ICML
2006
IEEE
16 years 7 months ago
Hidden process models
We introduce Hidden Process Models (HPMs), a class of probabilistic models for multivariate time series data. The design of HPMs has been motivated by the challenges of modeling h...
Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rus...
DCC
2007
IEEE
16 years 6 months ago
A Stochastic Model for Video and its Information Rates
We propose a stochastic model for video and compute its information rates. The model has two sources of information representing ensembles of camera motion and visual scene data (...
Arthur L. da Cunha, Minh N. Do, Martin Vetterli