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VLSM
2005
Springer
15 years 3 months ago
Entropy Controlled Gauss-Markov Random Measure Field Models for Early Vision
We present a computationally efficient segmentationrestoration method, based on a probabilistic formulation, for the joint estimation of the label map (segmentation) and the para...
Mariano Rivera, Omar Ocegueda, José L. Marr...
IWCMC
2010
ACM
14 years 11 months ago
On the use of random neural networks for traffic matrix estimation in large-scale IP networks
Despite a large body of literature and methods devoted to the Traffic Matrix (TM) estimation problem, the inference of traffic flows volume from aggregated data still represents a ...
Pedro Casas, Sandrine Vaton
EMNLP
2004
14 years 11 months ago
Applying Conditional Random Fields to Japanese Morphological Analysis
This paper presents Japanese morphological analysis based on conditional random fields (CRFs). Previous work in CRFs assumed that observation sequence (word) boundaries were fixed...
Taku Kudo, Kaoru Yamamoto, Yuji Matsumoto
TPDS
2010
135views more  TPDS 2010»
14 years 8 months ago
Maximizing Service Reliability in Distributed Computing Systems with Random Node Failures: Theory and Implementation
—In distributed computing systems (DCSs) where server nodes can fail permanently with nonzero probability, the system performance can be assessed by means of the service reliabil...
Jorge E. Pezoa, Sagar Dhakal, Majeed M. Hayat
CVPR
2011
IEEE
14 years 6 months ago
Using Global Bag of Features Models in Random Fields for Joint Categorization and Segmentation of Objects
We propose to bridge the gap between Random Field (RF) formulations for joint categorization and segmentation (JCaS), which model local interactions among pixels and superpixels, ...
Dheeraj Singaraju, René, Vidal