This paper proposes a hierarchical random field model for segmentation of images.
本文提出了一种用于图像分割的分层随机场模型。
Firstly, maximum a posteriori framework is created according to conditional random field model and Markov random field model.
根据条件随机场模型和马尔可夫随机场模型建立了一个最大后验概率框架。
For many sample-based texture synthesis algorithms using markov random field model, the size of neighborhood determines the quality and speed of texture synthesis.
在许多采用马尔可夫随机场模型的基于样图的纹理合成算法中，邻域的大小决定着这些合成算法的纹理合成质量和合成速度。
In this paper, a kind of generalized multiscale fractal parameter is proposed and constructed for the description of image textures, which is based on fractional Brownian random field model.
本文从分数布朗随机场模型的描述出发，提出并构造了一种广义多尺度分形参数，用于描述图像的纹理信息。
Utilizing MRF (Markov Random Field) model to introduce the pixel's local context information, a quite accurate segmentation of SAR target chip image is realized.
文中通过利用马尔可夫随机场模型，引入图像象素的局部结构信息，有效实现了SAR目标切片图像的高精度分割。
So Conditional Random Field (CRF) is introduced to build POS tagging model in this paper, in order to overcome above problems.
论文引入条件随机域建立词性标注模型，易于融合新的特征，并能解决标注偏置的问题。
In this way, corresponding to every single viscoelastic random medium model, we can calculate and gained 6 different wave field characteristic quantities.
这样，对应每一个粘弹性随机介质模型，我们均可计算得到6个不同的波场特征量。
A combined method based on Markov Random Field (MRF) model and morphological operation was presented for the segmentation of the SAR image in target monitoring.
针对目标监测分析中的SAR图像分割问题，构造了一种基于马尔可夫随机场(MRF)模型和形态学运算的处理方法。
The model indicates that three types of parameters affect the ADCP discharge measurement random uncertainty: ADCP system parameters, river hydraulic parameters and field operation parameters.
该模型表明，影响ADCP流量测验随机不确定度的参数可以分为三类：即adcp系统性能参数、河流水力参数、测验作业参数。
A fuzzy Markov random field (FMRF) model is established and a new algorithm based on FMRF for image segmentation proposed in this paper.
本文建立模糊马尔可夫场模型，并提出基于模糊马尔可夫场的图像分割新算法。
In this way, corresponding to every single transversely isotropic elastic random medium model, we can calculate and gained 15 different wave field characteristic quantities.
这样，对应每一个横各向同性弹性随机介质模型，均可计算得到15个不同的波场特征量。
A random synthesis procedure based on finite fault model is adopted for near field strong ground motion simulation, in this paper.
为了模拟近场强地震动，采用了基于有限断层模型的一种随机合成方法。
This paper presents a novel unsupervised image segmentation algorithm based on hidden Markov random field(HMRF) model.
研究了基于隐马尔可夫随机场（HMRF）模型的无监督图像分割问题。
In our method, we transformed the problem into an equivalent sequence tagging problem, and built up the automatic generation model through the first order conditional random field.
我们的方法是将简称生成问题转化为等价的序列标注问题，并利用一阶条件随机场建立自动生成模型。
We investigate the fluctuation of price process in a stock market with Ising model and the mean field theory, and construct the corresponding random logarithmic price returns process.
再利用计算机模拟股票价格收益率的分布特征，模型很好的刻画了现实证券市场中股票收益率分布的宽尾现象、长记忆性，以及累积分布中尾部收益的指数递减现象。
We adopt the coupling Discrete Random Walk Model for the study of the two-phase flow-field.
在两相流的研究中采用了相间耦合的随机轨道模型。
By using the multi resolution analysis to interpolate the mean values based on hierachical model of Gibbs random field, a method for binary sketch of grey imagre was proposed.
根据分层吉布斯随机场模型，采用小波函数分级拟合均值曲面，提出了二值化方法。
This paper proposes a Markov random field(MRF) model-based approach to natural image matting with complex scenes.
为了取得更好的抠图效果，提出了一种基于马尔可夫随机场的自然图像抠图方法。
Secondly, this paper proposed a method combined rule-based pos selection model with Statistics-based Cascading Conditional random field to conduct semantic Role Labeling of Chinese Question.
其次，本文选用了一种将基于统计方法的条件随机场模型与基于规则方法的词性筛选模型相结合的方式对中文问句进行语义角色自动标注。
Secondly, this paper proposed a method combined rule-based pos selection model with Statistics-based Cascading Conditional random field to conduct semantic Role Labeling of Chinese Question.
其次，本文选用了一种将基于统计方法的条件随机场模型与基于规则方法的词性筛选模型相结合的方式对中文问句进行语义角色自动标注。
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