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- Maximum likelihood classifier (MLC) is the most used and effective classification method. 最大似然法分是常规遥感图像最常用、最有效的分类方法。
- According to the method classification test is done with ETM data, and the accuracy is compared with the one of maximum likelihood classifier. 结果表明,利用基于支持向量机的方法进行遥感图像分类,精度明显优于最大似然法分类的精度。
- Gaussian Maximum Likelihood Classifier 高斯最大似然分类
- The EM-based Maximum Likelihood Classifier for Remotely Sensed Data 遥感图像最大似然分类方法的EM改进算法
- maximum likelihood classifier 极大似然分类器
- The second goal is the estimation method of maximum likelihood. 第二个目标是最大似然的估计方法。
- To learn a classifier,a semisupervised Bayesian approach is adopted.An EM algorithm is derived to compute maximum likelihood estimate.Experimental results demonstrate appropriate accuracy. 分类器的学习采用半监督贝叶斯方法;使用EM算法求解最大似然估计;实验结果表明能够获得较好的结果.
- To learn a classifier, a semisupervised Bayesian approach is adopted. An EM algorithm is derived to compute maximum likelihood estimate. Experimental results demonstrate appropriate accuracy. 摘要分类器的学习采用半监督贝叶斯方法,使用EM算法求解最大似然估计,实验结果表明能够获得较好的结果。
- And then the model parameters are estimated by means of MLE (maximum likelihood estimation). 其次运用极大似然估计方法对模型的参数进行标定。
- The result showed that the maximum likelihood algorithm possesses higher stability and suitability on the random measured noise. 结果表明极大似然算法对随机测量噪声具有更高的稳定性和适应性。
- Empirical Bayes estimation (EBE) and maximum likelihood estimation (MLE) of reliability index are given, respectively. 分别给出了系统可靠性指标的经验 Bayes 估计,极大似然估计。
- In this paper, the maximum likelihood esti mati on and Bayesian estimation of parameter N are obtained. 本文推导出了 N的极大似然估计 Bayes估计 .
- The maximum likelihood estimates (MLEs) of the model are computed with the EM algorithm. 本文将其中一个扰动变量视为缺失数据,利用EM算法得到模型参数的极大似然估计。
- Parameters of AR PSD Model can be obtained by maximum likelihood estimate (MLE). AR模型参数估计可以使用最大似然估计法(MLE);
- An alternative criterion is to minimise the generalised maximum likelihood (GML) developed by Wahba (1985,1990). 另一标准是Wahba(1985,1990)发展的最小广义最大似然法。
- Permutation configurations are optimized while jointly modeling many images via maximum likelihood. 通过极大似然方法可以对多图像的置换(矩阵)进行优化。
- An improved maximum likelihood estimation method named AMLE was proposed in this paper. 其根本原因是没有考虑每个点对固有维数的不同贡献。
- This paper utilizes the maximum likelihood to estimate the parameters of the choice model. 利用最大似然法,对模型的上下选择层的参数进行估计。
- At last, transporter restarder fatigue curve based on maximum likelihood method was validate by tseting data. 最后,通过输送机疲劳试验的实测结果对疲劳曲线的标定方法进行了验证。
- The distribution parameters have been estimated with either the maximum likelihood method or a modified moment method. 对其中的参数分别用极大似然法和改进的矩法进行了估计。