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» Robust background modeling via standard variance feature
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MCS
2010
Springer
13 years 8 months ago
Tomographic Considerations in Ensemble Bias/Variance Decomposition
Abstract. Classifier decision fusion has been shown to act in a manner analogous to the back-projection of Radon transformations when individual classifier feature sets are non o...
David Windridge
ICASSP
2010
IEEE
13 years 6 months ago
Acoustic model adaptation via Linear Spline Interpolation for robust speech recognition
We recently proposed a new algorithm to perform acoustic model adaptation to noisy environments called Linear Spline Interpolation (LSI). In this method, the nonlinear relationshi...
Michael L. Seltzer, Alex Acero, Kaustubh Kalgaonka...
ICPR
2006
IEEE
14 years 10 days ago
A Pixel-wise Object Tracking Algorithm with Target and Background Sample
In this paper, we present a clustering-based tracking algorithm for non-rigid object. Non-rigid object tracking is a challenging task because the target often appears as a concave...
Chunsheng Hua, Haiyuan Wu, Qian Chen, Toshikazu Wa...
ICPR
2008
IEEE
14 years 22 days ago
Pedestrian detection by modeling local convex shape features
This paper presents a pedestrian model built collectively on a group of strong local convex shape descriptors. The pedestrian model captures the most important features of a pedes...
Jungme Park, Yun Luo, Haoxing Wang, Yi Lu Murphey
BMCBI
2007
138views more  BMCBI 2007»
13 years 6 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...