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12_Models_For_Grids

12_Models_For_Grids

魏先生
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Consider models with one unknown world state at each pixel in the image – takes the form of a grid. Loops in the graphical model, so cannot use dynamic programming or belief propagation Define probability distributions that favor certain configurations of world states Called Markov random fields Inference using a set of techniques called graph cuts
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