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VLSM
2005
Springer
14 years 2 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...
SIGGRAPH
1996
ACM
14 years 19 days ago
Real-Time, Continuous Level of Detail Rendering of Height Fields
We present an algorithm for real-time level of detail reduction and display of high-complexity polygonal surface data. The algorithm uses a compact and efficient regular grid repr...
Peter Lindstrom, David Koller, William Ribarsky, L...
EMNLP
2004
13 years 10 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
ICASSP
2010
IEEE
13 years 8 months ago
Language recognition using deep-structured conditional random fields
We present a novel language identification technique using our recently developed deep-structured conditional random fields (CRFs). The deep-structured CRF is a multi-layer CRF mo...
Dong Yu, Shizhen Wang, Zahi Karam, Li Deng
TIP
2008
139views more  TIP 2008»
13 years 8 months ago
Model-Based 2.5-D Deconvolution for Extended Depth of Field in Brightfield Microscopy
Abstract--Due to the limited depth of field of brightfield microscopes, it is usually impossible to image thick specimens entirely in focus. By optically sectioning the specimen, t...
François Aguet, Dimitri Van De Ville, Micha...