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研究马尔科夫随机场和吉布斯随机场理论之间关系的文章，有严格的推理。希望对大家有用-Of Markov random fields and Gibbs random field theory of the relationship between the articles, there are strict reasoning. Hope to useful
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该方法实现了一种实时的由粗到细的超像素分割,是cvpr2015的一篇paper，该方法的效果非日常的好。指得大家学习和借鉴。-In this paper, we tackle the problem of unsupervised segmentation in the form of superpixels. Our main emphasis is
on speed and accuracy. We build on [31] to define the problem as a bou
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基于马尔可夫随机场模型的SAR图像变换检测源码-SAR image based on change detection Source Markov random field model
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this code contains MRF optimization with Fast PD - and it can be used as a tool for minimizing the energy of a discrete Markov Random Field (MRF).
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一篇经典的描述多层次马尔科夫随机场分割影像的paper(A classic paper describing multilevel Markov random field segmentation images)
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马尔科夫随机场一般是离散的。当然也有连续的马尔可夫随机场，如果假设这个马尔可夫随机场定义在一个域U上面而且任意x∈U，Y(x)都是服从高斯分布的，而且两点间的covariance function K(x,y)=G(x,y)，where G是对应U的格林函数，那么这个随机场既是马尔可夫随机场，也是高斯随机场。(The Markov random field is generally discrete. Of course there are continuous Markov random fi
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