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ICVGIP
2004
14 years 11 months ago
A Robust Nonparametric Estimation Framework for Implicit Image Models
Robust model fitting is important for computer vision tasks due to the occurrence of multiple model instances, and, unknown nature of noise. The linear errors-in-variables (EIV) m...
Himanshu Arora, Maneesh Singh, Narendra Ahuja
BMCBI
2011
14 years 4 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso
117
Voted
ICANN
2009
Springer
15 years 2 months ago
Bayesian Estimation of Kernel Bandwidth for Nonparametric Modelling
Kernel density estimation (KDE) has been used in many computational intelligence and computer vision applications. In this paper we propose a Bayesian estimation method for findin...
Adrian G. Bors, Nikolaos Nasios
CVPR
1997
IEEE
15 years 1 months ago
Smoothness in Layers: Motion segmentation using nonparametric mixture estimation
Grouping based on common motion, or “common fate” provides a powerful cue for segmenting image sequences. Recently a number of algorithms have been developed that successfully...
Yair Weiss
DATE
2008
IEEE
226views Hardware» more  DATE 2008»
15 years 4 months ago
A General Method to Evaluate RF BIST Techniques Based on Non-parametric Density Estimation
Abstract— We present a general method to evaluate RF BuiltIn Self-Test (BIST) techniques during the design stage. In particular, the adaptive kernel estimator is used to construc...
Haralampos-G. D. Stratigopoulos, Jeanne Tongbong, ...