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138
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BMCBI
2005
98views more  BMCBI 2005»
15 years 4 months ago
The effects of normalization on the correlation structure of microarray data
Background: Stochastic dependence between gene expression levels in microarray data is of critical importance for the methods of statistical inference that resort to pooling test-...
Xing Qiu, Andrew I. Brooks, Lev Klebanov, Andrei Y...
160
Voted
BMCBI
2010
229views more  BMCBI 2010»
15 years 4 months ago
Mocapy++ - A toolkit for inference and learning in dynamic Bayesian networks
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Martin Paluszewski, Thomas Hamelryck
ICCV
1998
IEEE
16 years 6 months ago
Consensus Surfaces for Modeling 3D Objects from Multiple Range Images
In this paper, we present a robust method for creating a triangulated surface mesh from multiple range images. Our method merges a set of range images into a volumetric implicit-s...
Mark D. Wheeler, Yoichi Sato, Katsushi Ikeuchi
ICIP
2007
IEEE
16 years 6 months ago
A HMM-Based Method for Recognizing Dynamic Video Contents from Trajectories
This paper describes an original method for classifying object motion trajectories in video sequences in order to recognize dynamic events. Similarities between trajectories are e...
Alexandre Hervieu, Patrick Bouthemy, Jean-Pierre L...
214
Voted
ICCV
2011
IEEE
14 years 4 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