• 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马尔可夫随机场模型建立了最大后验概率框架

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  • So Conditional Random Field (CRF) is introduced to build POS tagging model in this paper, in order to overcome above problems.

    论文引入条件随机建立词性标注模型,易于融合新的特征,并解决标注偏置的问题

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  • 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.

    我们方法是将简称生成问题转化等价序列标注问题,利用条件随机场建立自动生成模型

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  • A regularized image restoration is the optimization for some conditional constraint, and the selection of wavelet coefficients based Bayesian statistic is on the image random field view.

    正则图像恢复条件约束最优化问题,小波系数贝叶斯统计选择基于图像的机场观点。

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  • A regularized image restoration is the optimization for some conditional constraint, and the selection of wavelet coefficients based Bayesian statistic is on the image random field view.

    正则图像恢复条件约束最优化问题,小波系数贝叶斯统计选择基于图像的机场观点。

    youdao

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