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INFOCOM
2003
IEEE
13 years 12 months ago
Pseudo Likelihood Estimation in Network Tomography
Abstract— Network monitoring and diagnosis are key to improving network performance. The difficulties of performance monitoring lie in today’s fast growing Internet, accompani...
Gang Liang, Bin Yu
CORR
2010
Springer
103views Education» more  CORR 2010»
13 years 6 months ago
Spatially-Adaptive Reconstruction in Computed Tomography Based on Statistical Learning
We propose a direct reconstruction algorithm for Computed Tomography, based on a local fusion of a few preliminary image estimates by means of a non-linear fusion rule. One such ru...
Joseph Shtok, Michael Zibulevsky, Michael Elad
CVPR
1997
IEEE
13 years 11 months ago
Using Local 3D Structure for Segmentation of Bone from Computer Tomography Images
In this paper we focus on using local 3D structure for segmentation. A tensor descriptor is estimated for each neighbourhood, i.e. for each voxel in the data set. The tensors are ...
Carl-Fredrik Westin, Abhir Bhalerao, Ron Kikinis, ...
FLAIRS
1998
13 years 8 months ago
An AI Approach to Computer Assisted Tomography
Computer assisted tomography (CAT) systems demandlarge amounts of time and space. In this paper, wedescribe an approachto solving the CAT problemusing several AItechniques includi...
John F. Kolen, David A. Shamma, Thomas Reichherzer...
ICASSP
2011
IEEE
12 years 10 months ago
Variational methods for spectral unmixing of hyperspectral images
This paper studies a variational Bayesian unmixing algorithm for hyperspectral images based on the standard linear mixing model. Each pixel of the image is modeled as a linear com...
Olivier Eches, Nicolas Dobigeon, Jean-Yves Tourner...