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ICCV
2011
IEEE
12 years 7 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
ICCVW
1999
Springer
13 years 11 months ago
Optimization Criteria, Sensitivity and Robustness of Motion and Structure Estimation
The prevailing efforts to study the standard formulation of motion and structure recovery have been recently focused on issues of sensitivity and and robustness of existing techn...
Jana Kosecka, Yi Ma, Shankar Sastry
BMCBI
2010
140views more  BMCBI 2010»
13 years 7 months ago
Quantification and deconvolution of asymmetric LC-MS peaks using the bi-Gaussian mixture model and statistical model selection
Background: Liquid chromatography-mass spectrometry (LC-MS) is one of the major techniques for the quantification of metabolites in complex biological samples. Peak modeling is on...
Tianwei Yu, Hesen Peng
ICIP
2008
IEEE
14 years 8 months ago
Multiple description video decoding using map
The problem of efficient video transmission over noisy channels involves good compression rates and robustness in presence of channel failures. The proposed framework of joint sou...
Marc Antonini, Marie Andrée Agostini
ICASSP
2010
IEEE
13 years 7 months ago
Nonlinear kernel backprojection for computed tomography
In this paper, we propose a kernel backprojection method for computed tomography. The classical backprojection method estimates an unknown pixel value by the summation of the proj...
Hiroyuki Takeda, Peyman Milanfar