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» Hierarchical Clustering of a Mixture Model
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BMCBI
2007
133views more  BMCBI 2007»
13 years 8 months ago
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
PAMI
2011
13 years 2 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
MICCAI
2009
Springer
14 years 9 months ago
Functional Segmentation of fMRI Data Using Adaptive Non-negative Sparse PCA (ANSPCA)
We propose a novel method for functional segmentation of fMRI data that incorporates multiple functional attributes such as activation effects and functional connectivity, under a ...
Bernard Ng, Rafeef Abugharbieh, Martin J. McKeow...
ICIP
2005
IEEE
14 years 1 months ago
HMM-based motion recognition system using segmented PCA
In this paper, we propose a novel technique for modelbased recognition of complex object motion trajectories using Hidden Markov Models (HMM). We build our models on Principal Com...
Faisal I. Bashir, Wei Qu, Ashfaq A. Khokhar, Dan S...
ECCV
2004
Springer
14 years 1 months ago
Probabilistic Spatial-Temporal Segmentation of Multiple Sclerosis Lesions
Abstract. In this paper we describe the application of a novel statistical videomodeling scheme to sequences of multiple sclerosis (MS) images taken over time. The analysis of the ...
Allon Shahar, Hayit Greenspan