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ECCV
2008
Springer
14 years 9 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
RECOMB
2005
Springer
14 years 8 months ago
Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition
Abstract. Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e. segmenta...
Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanath...
CORR
2008
Springer
167views Education» more  CORR 2008»
13 years 7 months ago
Energy Scaling Laws for Distributed Inference in Random Networks
The energy scaling laws of multihop data fusion networks for distributed inference are considered. The fusion network consists of randomly located sensors independently distributed...
Animashree Anandkumar, Joseph E. Yukich, Lang Tong...
JCB
2006
215views more  JCB 2006»
13 years 7 months ago
Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs)
Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e., segmentation con...
Yan Liu 0002, Jaime G. Carbonell, Peter Weigele, V...
GLOBECOM
2009
IEEE
14 years 2 months ago
Random Linear Network Coding for Time-Division Duplexing: Field Size Considerations
Abstract— We study the effect of the field size on the performance of random linear network coding for time division duplexing channels proposed in [1]. In particular, we study ...
Daniel Enrique Lucani, Muriel Médard, Milic...