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CVPR
2012
IEEE
11 years 11 months ago
Background segmentation with feedback: The Pixel-Based Adaptive Segmenter
In this paper we present a novel method for foreground segmentation. Our proposed approach follows a nonparametric background modeling paradigm, thus the background is modeled by ...
Martin Hofmann 0011, Philipp Tiefenbacher, Gerhard...
JMLR
2010
132views more  JMLR 2010»
13 years 3 months ago
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mu...
ICPR
2002
IEEE
14 years 9 months ago
Linear and Non-Linear Model for Statistical Localization of Landmarks
This paper presents and compares 3 methods for the statistical localization of partially occulted landmarks. In many real applications, some information is visible in images and s...
Barbara Romaniuk, Michel Desvignes, Marinette Reve...
WSC
1998
13 years 10 months ago
Properties of Synthetic Optimization Problems
In this paper, we present an approach for measuring certain properties of synthetic optimization problems based on the assumed distribution of coefficient values. We show how to e...
Charles H. Reilly
BMCBI
2007
125views more  BMCBI 2007»
13 years 8 months ago
Bayesian meta-analysis models for microarray data: a comparative study
Background: With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis...
Erin M. Conlon, Joon J. Song, Anna Liu