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» Linear State-Space Models for Blind Source Separation
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ICCV
2009
IEEE
13 years 5 months ago
Component analysis approach to estimation of tissue intensity distributions of 3D images
Many segmentation problems in medical imaging rely on accurate modeling and estimation of tissue intensity probability density functions. Gaussian mixture modeling, currently the ...
Arridhana Ciptadi, Cheng Chen, Vitali Zagorodnov
TAOSD
2010
13 years 6 months ago
A Graph-Based Aspect Interference Detection Approach for UML-Based Aspect-Oriented Models
Abstract. Aspect Oriented Modeling (AOM) techniques facilitate separate modeling of concerns and allow for a more flexible composition of these than traditional modeling technique...
Selim Ciraci, Wilke Havinga, Mehmet Aksit, Christo...
NIPS
1997
13 years 9 months ago
Extended ICA Removes Artifacts from Electroencephalographic Recordings
Severe contamination of electroencephalographic (EEG) activity by eye movements, blinks, muscle, heart and line noise is a serious problem for EEG interpretation and analysis. Rej...
Tzyy-Ping Jung, Colin Humphries, Te-Won Lee, Scott...
BMCBI
2006
203views more  BMCBI 2006»
13 years 7 months ago
Independent component analysis reveals new and biologically significant structures in micro array data
Background: An alternative to standard approaches to uncover biologically meaningful structures in micro array data is to treat the data as a blind source separation (BSS) problem...
Attila Frigyesi, Srinivas Veerla, David Lindgren, ...
ECML
2006
Springer
13 years 11 months ago
Deconvolutive Clustering of Markov States
In this paper we formulate the problem of grouping the states of a discrete Markov chain of arbitrary order simultaneously with deconvolving its transition probabilities. As the na...
Ata Kabán, Xin Wang