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这是一个马尔科夫随机场的代码，能够轻松的测试程序效果-This is the code of a Markov random field can easily test program effect
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西工大的一篇关于MRF的论文。该论文提出了一种新颖的基于马尔可夫随机场(MRF) 空间上下文信息的图象分割方法。-NPU a papers on MRF. This paper presents a novel based on Markov random field ( MRF ) the spatial context information of the image segmentation method.
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提出了一种基于MAP的Markov随机场的图像融合方法-This paper proposes a method of Markov random field to classify the remote sensing images based on the maxi-
mum a posteriori model
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主要用是马尔可夫随机场分割问题，采用ICM迭代方法。-Mainly with Markov random field segmentation using ICM iterative method.
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指纹分类是针对大型指纹库的一个重要的索引方式, 可以有效地提高指纹匹配的效率. 指纹类型的不同表现为指纹纹
理结构的差异, 而指纹的方向场则可以有效地描述纹理结构的差异. 同一类型指纹不同区域上方向角结构的差异以及相邻区域
间方向角结构的联系可以视作一个马尔可夫随机场. 本文利用嵌入式隐马尔可夫模型对指纹方向场进行建模分析, 通过合理地
抽取指纹的类型特征, 构造观察向量、进行建模训练, 然后利用训练好的马尔可夫模型进行匹配, 最终提出并实现了一种新的鲁
棒性强且精度较高的指纹分
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吉布斯分布代码，常用于马尔科夫随机场分割和识别-Gibbs distribution code, commonly used for Markov Random Field segmentation and recognition
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压缩感知中置信传播和马尔可夫随机场的全部源代码-Compressed sensing belief propagation and Markov random field full source code
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利用马尔科夫随机场和吉布斯分布来进行图像处理，将图像分为不同区域-The use of markov random field and gibbs distribution for image processing, image can be divided into different areas
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通过Markov随机场（MRF）实现图像的分割，例程给出了图像分割为3类的MRF算法-By Markov random field (MRF) for image segmentation, image segmentation routine gives the MRF algorithm for the three classes
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A non-parametric method for texture synthesis proposed.
The texture synthesis process grows a new image
outward from an initial seed, one pixel at a time. A Markov
random field model is assumed, and the conditional distribution
of a pixel giv
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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,
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markov random field in C-markov random field in C++
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基于马尔科夫随机场的过绿色模拟退火的分割方法程序，包含如何建立马尔科夫随机场。-Markov random field segmentation method for green program based on simulated annealing, including how to build the Markov random field.
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使用马尔可夫随机场进行图像分割，包括标记场、特征场建模和参数估计等，程序可运行。-image segmentation Using Markov random field , including label Field, features field modeling and parameter estimation, the program can run.
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将置信传播(belief propagation,BP)算法从马尔科夫随机域的角度进行理解，
并通过变量节点和校验界定之间的迭代来实现信息传递，进而提高系统的误码率性能。
-The belief propagation (belief propagation, BP) algorithm is understood from the perspective of Markov random field, and by defining the iteration variable nod
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置信传播算法可通过因子图的角度理解，也可通过马尔科夫随机域的思想来理解，不管从哪个角度实现，都可将其应用于检测，提高性能。-Belief propagation algorithm can be understood by the angle factor graph can also be understood by thinking of Markov random field, regardless of the angle from which to achieve, can be ap
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马尔可夫随机场的图像分割，本人整理的代码和论文-Markov random field image segmentation, I am finishing the code and papers
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一种基于马尔科夫随机场的图像分割matlab源码，包含ICM迭代条件模式求解最大后验概率算法，已通过测试。-Markov random field based image segmentation matlab source code, including the ICM iteration conditions for solving the maximum a posteriori probability model algorithm has been tested.
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In this paper we present Discriminative Random Fields (DRF), a discrim- inative framework for the classification of natural image regions by incor- porating neighborhood spatial dependencies in the labels as well as the observed data. The proposed mo
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马尔科夫随机场模型程序。已经运行过了，可以使用-Markov random field model program. Has been run, you can use
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