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» Query segmentation using conditional random fields
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ICCV
2011
IEEE
13 years 9 months ago
Are Spatial and Global Constraints Really Necessary for Segmentation?
Many state-of-the-art segmentation algorithms rely on Markov or Conditional Random Field models designed to enforce spatial and global consistency constraints. This is often accom...
Aurelien Lucchi, Yunpeng Li, Xavier Boix, Kevin Sm...
AAAI
2008
15 years 13 hour ago
Constrained Classification on Structured Data
Most standard learning algorithms, such as Logistic Regression (LR) and the Support Vector Machine (SVM), are designed to deal with i.i.d. (independent and identically distributed...
Chi-Hoon Lee, Matthew R. G. Brown, Russell Greiner...
CVPR
2012
IEEE
13 years 3 days ago
Joint 2D-3D temporally consistent semantic segmentation of street scenes
In this paper we propose a novel Conditional Random Field (CRF) formulation for the semantic scene labeling problem which is able to enforce temporal consistency between consecuti...
Georgios Floros, Bastian Leibe
83
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SAC
2003
ACM
15 years 2 months ago
A Markov Random Field Model of Microarray Gridding
DNA microarray hybridisation is a popular high throughput technique in academic as well as industrial functional genomics research. In this paper we present a new approach to auto...
Mathias Katzer, Franz Kummert, Gerhard Sagerer
MICCAI
2004
Springer
15 years 10 months ago
3D Bayesian Regularization of Diffusion Tensor MRI Using Multivariate Gaussian Markov Random Fields
3D Bayesian regularization applied to diffusion tensor MRI is presented here. The approach uses Markov Random Field ideas and is based upon the definition of a 3D neighborhood syst...
Marcos Martín-Fernández, Carl-Fredri...