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» Monte Carlo Localization Using SIFT Features
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CVPR
2007
IEEE
15 years 11 months ago
What makes a good model of natural images?
Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
Yair Weiss, William T. Freeman
RTSS
2005
IEEE
15 years 3 months ago
Building Robust Wireless LAN for Industrial Control with DSSS-CDMA Cellphone Network Paradigm
Deploying Wireless LAN for Industrial Control (ICWLAN) has many benefits, such as mobility, low deployment cost and ease of reconfiguration. However, the top concern is robustne...
Qixin Wang, Xue Liu, Weiqun Chen, Wenbo He, Marco ...
SIAMAM
2008
79views more  SIAMAM 2008»
14 years 9 months ago
Transport-Based Imaging in Random Media
This paper generalizes well-established derivations of the radiative transfer equation from first principles to model the energy density of time-dependent and monochromatic high f...
Guillaume Bal, Kui Ren
FOCS
2008
IEEE
15 years 4 months ago
Mixing Time of Exponential Random Graphs
A plethora of random graph models have been developed in recent years to study a range of problems on networks, driven by the wide availability of data from many social, telecommu...
Shankar Bhamidi, Guy Bresler, Allan Sly
SIGGRAPH
1997
ACM
15 years 1 months ago
Metropolis light transport
We present a new Monte Carlo method for solving the light transport problem, inspired by the Metropolis sampling method in computational physics. To render an image, we generate a...
Eric Veach, Leonidas J. Guibas