Hidden Conditional Random Fields
Copyright policy )Hidden Conditional Random Fields
We present a discriminative latent variable model for classification problems in structured domains where inputs can be represented by a graph of local observations. A hidden-state Conditional Random Field framework learns a set of latent variables conditioned on local features. Observations need not be independent and may overlap in space and time.
- Massachusetts Institute of Technology United States
Models, Statistical, Reproducibility of Results, Image Enhancement, Sensitivity and Specificity, Markov Chains, Pattern Recognition, Automated, Artificial Intelligence, Data Interpretation, Statistical, Image Interpretation, Computer-Assisted, Computer Simulation, Algorithms
Models, Statistical, Reproducibility of Results, Image Enhancement, Sensitivity and Specificity, Markov Chains, Pattern Recognition, Automated, Artificial Intelligence, Data Interpretation, Statistical, Image Interpretation, Computer-Assisted, Computer Simulation, Algorithms
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