Continuous Conditional Random Fields for Regression in Remote Sensing

  title={Continuous Conditional Random Fields for Regression in Remote Sensing},
  author={Vladan Radosavljevic and Slobodan Vucetic and Zoran Obradovic},
Conditional random fields (CRF) are widely used for predicting output variables that have some internal structure. Most of the CRF research has been done on structured classification where the outputs are discrete. In this study we propose a CRF probabilistic model for structured regression that uses multiple non-structured predictors as its features. We construct features as squared prediction errors and show that this results in a Gaussian predictor. Learning becomes a convex optimization… CONTINUE READING
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