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» Graph model selection using maximum likelihood
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MICCAI
2005
Springer
16 years 19 days ago
Tissue Classification of Noisy MR Brain Images Using Constrained GMM
We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of G...
Amit Ruf, Hayit Greenspan, Jacob Goldberger
81
Voted
ICMI
2003
Springer
99views Biometrics» more  ICMI 2003»
15 years 5 months ago
Using an autonomous cube for basic navigation and input
This paper presents a low-cost and practical approach to achieve basic input using a tactile cube-shaped object, augmented with a set of sensors, processor, batteries and wireless...
Kristof Van Laerhoven, Nicolas Villar, Albrecht Sc...
IPPS
2006
IEEE
15 years 5 months ago
Phylogenetic models of rate heterogeneity: a high performance computing perspective
Inference of phylogenetic trees using the maximum likelihood (ML) method is NP-hard. Furthermore, the computation of the likelihood function for huge trees of more than 1,000 orga...
Alexandros Stamatakis
ACL
2010
14 years 9 months ago
Viterbi Training for PCFGs: Hardness Results and Competitiveness of Uniform Initialization
We consider the search for a maximum likelihood assignment of hidden derivations and grammar weights for a probabilistic context-free grammar, the problem approximately solved by ...
Shay B. Cohen, Noah A. Smith
97
Voted
CVPR
2008
IEEE
16 years 1 months ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...