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TSP
2010
14 years 10 months ago
Variance-component based sparse signal reconstruction and model selection
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
Kun Qiu, Aleksandar Dogandzic
167
Voted
MICCAI
2008
Springer
16 years 4 months ago
A Discriminative Model-Constrained Graph Cuts Approach to Fully Automated Pediatric Brain Tumor Segmentation in 3-D MRI
In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation app...
Michael Wels, Gustavo Carneiro, Alexander Aplas,...
110
Voted
MOBIHOC
2005
ACM
16 years 3 months ago
Temporal properties of low power wireless links: modeling and implications on multi-hop routing
Recently, several studies have analyzed the statistical properties of low power wireless links in real environments, clearly demonstrating the differences between experimentally o...
Alberto Cerpa, Jennifer L. Wong, Miodrag Potkonjak...
164
Voted
CVPR
2009
IEEE
15 years 10 months ago
Robust shadow and illumination estimation using a mixture model
Illuminant estimation from shadows typically relies on accurate segmentation of the shadows and knowledge of exact 3D geometry, while shadow estimation is difficult in the presen...
Alexandros Panagopoulos, Dimitris Samaras, Nikos P...
ICASSP
2007
IEEE
15 years 10 months ago
Evolutionary Sequence Modeling for Discovery of Peptide Hormones
There are currently a large number of ‘‘orphan’’ G-protein-coupled receptors (GPCRs) whose endogenous ligands (peptide hormones) are unknown. Identification of these pepti...
M. Kemal Sönmez, Lawrence Toll, Nina Zaveri