本文提出了一种用于图像分割的分层随机场模型。
This paper proposes a hierarchical random field model for segmentation of images.
提出了一种基于马尔科夫随机场模型的缺陷检测方法。
A method of vane defects detecting based on Markov random field is presented in this paper.
引入土层剖面随机场模型，把土性参数的点变异性和空间变异性联系起来。
Point variability and spatial variability of soil property parameters are associated by means of stochastic field model of soil profile.
分析、设计和实现了一个基于条件随机场模型的汉语分词和词性标注模块。
We analyzed, designed and achieved a module of Chinese word segmentation and Part-Of-Speech Tagging based on Condition Random Fields 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。
Firstly, maximum a posteriori framework is created according to conditional random field model and Markov random field model.
针对旅游领域，提出了一种基于层叠条件随机场模型的旅游领域命名实体识别方法。
This paper presents a method for named entity recognition in the tourism domain based on the cascaded conditional random fields.
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。
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.
根据自然红外纹理在空间的统计分布特性，利用随机场模型可以有效地合成红外纹理。
The random field models can be available in synthesizing the natural texture according to the statistical distribution of intensity of texture in space.
在图像的多分辨率小波分析的基础上 ，采用高斯 -马尔可夫随机场模型来描述图像的局部特征 。
The hierarchical multiresolution wavelet analysis in conjunction with the contextual information of the image extracted from GMRF results in local features of the image.
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。
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.
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。
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.
我们利用条件随机场模型抽取领域实体对象，并将其应用于比较句识别和比较关系抽取中，取得了良好的实验效果。
We use CRF model to extract domain entities which are applied to identify comparative sentences and mine comparative relation with good results.
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。
For many sample-based texture synthesis algorithms using markov random field model, the size of neighborhood determines the quality and speed of texture synthesis.
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.
基于图像在小波域的马尔可夫随机场模型(MRF)结构，结合SAR图像中相干斑噪声的统计特性，本文提出了一种新的小波域相干斑抑制方法。
Integrating the statistical characteristics of speckle noise in SAR images with wavelet-domain Markov random field (MRF) structure of images, a new wavelet-domain spec.
针对遥感图像分布的不均匀性，该文提出的算法没有采用固定的马尔可夫随机场模型参数，而是在递归分类算法中分级地调整模型参数以适应区域的变化。
As the MRF model with fixed parameters does not fit the real remotely sensed image very well, this paper adjusts the MRF model "s parameters during the classification procedure."
针对遥感图像分布的不均匀特性，该文提出的算法没有采用固定的马尔可夫随机场模型参数，而是在递归分类算法中分级地调整模型参数以适应区域的变化。
As the MRF model with fixed parameters does not fit the real remotely sensed image very well, this paper adjusts the MRF model's parameters during the classification procedure.
采用传统图像检测方法存在目标区域定位不准确、目标细节信息丢失、目标形状变形等问题，本文提出一种基于离散分数布朗随机场模型的水下图像目标检测方法。
To overcome the shortcomings of traditional methods, a method of underwater image segmentation based on the discrete fractional Brownian random field was proposed to dispose underwater images.
条件随机场是一种无向图模型，它具有产生式模型和最大熵马尔可夫模型的优点。
Conditional Random Fields (CRF) is arbitrary undirected graphical model that bring together the best of generative models and Maximum Entropy Markov models (MEMM).
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。
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.
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。
This paper presents a novel unsupervised image segmentation algorithm based on hidden Markov random field(HMRF) model.
本文在相位扩散模型的基础上，研究了随机场对简并四波混频输出强度的影响。
The effect of the stochastic field on the degenerate four-wave mixing signal intensity hag been studied basing on the phase-diffusion model.
本文系统的介绍了条件随机场的定义、模型结构、特征函数、参数估计及其训练方法等。
This text systematically introduces the definition of CRFs, structure of the CRFs model, feature functions, parameter estimate and training methods.
而后给出了条件随机场的定义、模型结构、势函数的定义、参数估计、训练方法和计算方法等。
Then give the definition of CRFs, model structure, the definition of potential function, parameter estimation, training methods and calculation methods.
针对马尔可夫随机场在红外图像分割方面存在的问题，给出了一种基于混合高斯模型的三马尔可夫场红外图像分割算法。
Due to the problems to infrared image segmentation using Markov random fields, a method for infrared image segmentation based on triplet Markov fields using mixture gauss model was proposed.
方法：根据马尔科夫随机场图像模型，利用最大后验概率准则(MA P)，提出一种迭代松弛分割算法。
Methods: Based on Markov random fields model of noise, a iteration algorithm was presented by using maximum a posteriori (MAP) criterion.
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。
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。
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.
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