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- Firstly,a maximum a posteriori framework is created according to conditional random field model and Markov random field model. 首先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。
- This paper presents an approach of CFN automatic tagging based on cascaded conditional random fields model. 提出了一种基于层叠条件随机场的CFN自动标注方法。
- This paper presents a probabilistic approach of person name recognition.First coarsely segment the text and then add the segment tags to conditional random fields model. 摘要本文提出了一种基于统计的中文人名识别方法，此方法使用最大概率分词模型对源句子进行粗切分，将粗切分信息融入到条件随机场模型中进行模型的训练。
- Experimental results show that conditional random fields model is an effective way on Chinese text chunking and the strict Independence hypothesis and the label bias problem are avoided. 实验结果表明，条件随机域在中文组块识别方面有效，并避免了严格的独立性假设和数据归纳偏置问题。
- Conditional Random Fields (CRFs), a recently introduced conditioned probabilistic model for labeling and segmenting sequential data, is a statistics-based machine learning model. 条件随机场是近年来提出的一种条件概率模型，主要用于序列标注和分割，是一个基于统计的机器学习方法。
- Conditional Random Fields (CRFs) 条件随机域
- hidden conditional random fields 隐条件随机场
- cascaded conditional random fields 层叠条件随机场
- mixed skip-chain conditional random fields 混合跳链条件随机场
- Research of applying conditional random fields to Chinese lexical analysis 应用条件随机场进行汉语词法分析研究
- A Chinese Part-of-speech Tagging Approach Using Conditional Random Fields 基于条件随机场(CRFs)的中文词性标注方法
- conditional random field 条件随机场
- Remote sensing imagesegmentation for nonstationary random field models[J]. 引用该论文 李峰;彭嘉雄;张翔.
- Markov random field in image analysis, written by Li Qing, an absolute classic! 马尔克夫随机场在图像分析中的应用，李子青写的，绝对经典！
- Recognition of Complex Maximal Length Noun Phrase Using Conditional Random Fields 基于条件随机域的复杂最长名词短语识别
- Automatic Recognition of Chinese Organization Name Based on Cascaded Conditional Random Fields 基于层叠条件随机场模型的中文机构名自动识别
- condition random field (CRF) 条件随机场
- Firstly, a rough motion template was obtained by motion detection based on Markov random field model and through post-processing. 该算法首先利用马尔可夫随机场模型的运动检测算法，得到运动目标的初始模板。
- In this paper, a novel method of moving object segmentation based on spatiotemporal Markov Random Field(MRE) is proposed. 该文提出一种新的基于时空马尔可夫随机场的运动目标分割技术。
- This paper uses an algorithm of motion segmentation combined motion estimation with Markov Random Field（MRF）. 采用一种将运动估计方法与马尔可夫随机场（MRF）模型相结合的运动分割方法。
