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» Robust Bayesian Mixture Modelling
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ICASSP
2010
IEEE
13 years 10 months ago
Image-quality prediction of synthetic aperture sonar imagery
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
David P. Williams
NIPS
2004
13 years 11 months ago
Sampling Methods for Unsupervised Learning
We present an algorithm to overcome the local maxima problem in estimating the parameters of mixture models. It combines existing approaches from both EM and a robust fitting algo...
Robert Fergus, Andrew Zisserman, Pietro Perona
CORR
2006
Springer
66views Education» more  CORR 2006»
13 years 10 months ago
MDL Denoising Revisited
We refine and extend an earlier MDL denoising criterion for wavelet-based denoising. We start by showing that the denoising problem can be reformulated as a clustering problem, whe...
Teemu Roos, Petri Myllymäki, Jorma Rissanen
ICASSP
2011
IEEE
13 years 1 months ago
Detecting moving objects from dynamic background with shadow removal
Background subtraction is commonly used to detect foreground objects in video surveillance. Traditional background subtraction methods are usually based on the assumption that the...
Shih-Chieh Wang, Te-Feng Su, Shang-Hong Lai
ICMCS
2006
IEEE
215views Multimedia» more  ICMCS 2006»
14 years 4 months ago
Experiential Sampling based Foreground/Background Segmentation for Video Surveillance
Segmentation of foreground and background has been an important research problem arising out of many applications including video surveillance. A method commonly used for segmenta...
Pradeep K. Atrey, Vinay Kumar, Anurag Kumar, Mohan...