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MICCAI
2010
Springer
13 years 6 months ago
Nonlinear Embedding towards Articulated Spine Shape Inference Using Higher-Order MRFs
In this paper we introduce a novel approach for inferring articulated spine models from images. A low-dimensional manifold embedding is created from a training set of prior mesh mo...
Samuel Kadoury, Nikos Paragios
IPMI
2005
Springer
14 years 8 months ago
3D Active Shape Models Using Gradient Descent Optimization of Description Length
Abstract. Active Shape Models are a popular method for segmenting three-dimensional medical images. To obtain the required landmark correspondences, various automatic approaches ha...
Tobias Heimann, Ivo Wolf, Tomos G. Williams, Hans-...
SUTC
2008
IEEE
14 years 2 months ago
Training Data Compression Algorithms and Reliability in Large Wireless Sensor Networks
With the availability of low-cost sensor nodes there have been many standards developed to integrate and network these nodes to form a reliable network allowing many different typ...
Vasanth Iyer, Rammurthy Garimella, M. B. Srinivas
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 8 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
CORR
2011
Springer
190views Education» more  CORR 2011»
12 years 11 months ago
Doubly Robust Smoothing of Dynamical Processes via Outlier Sparsity Constraints
Abstract—Coping with outliers contaminating dynamical processes is of major importance in various applications because mismatches from nominal models are not uncommon in practice...
Shahrokh Farahmand, Georgios B. Giannakis, Daniele...