Most recent approaches have posed texture synthesis in a statistical setting as a problem of sampling from a probability distribution. Zhu et. al. [12] model texture as a Markov Random Field and use Gibbs sampling for synthesis. Unfortunately, Gibbs sampling is notoriously slow and in fact it is not possible to assess when it has converged. Heeger and Bergen [6] try to coerce a random noise image.

HuntLinKulkarni-PredictingCourseGrades.pdf

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