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Expectation-Maximization
The EM (Expectation-Maximization) algorithm estimates the parameters of the multivariate probability density function in a form of the Gaussian mixture distribution with a specified number of mixtures.
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这是一篇详细介绍人脸检测与语音驱动口型的文章，其中使用了高斯混合模型采取了无监督聚类的方法，希望对你有用。,This is a detailed introduction Face Detection and voice-driven I-type article, which uses the Gaussian mixture model taken unsupervised clustering method, in the hope that useful to you.
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混合高斯建模是背景建模中的一种经典方法，对复杂背景具有较好的适应性！,Gaussian mixture modeling is modeling in the context of a classical method, the complex has better adaptability background!
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学位论文；运动物体跟踪方法主要包括卡尔曼滤波，Mean-shift，Camshifi算法，粒子滤波器，Snake模型等；应用卡尔曼滤波方法设计了一套煤矿矿工出入自动监测系统；提出了一种新的基于高斯混合模型的颜色特征提取方法，该方法克服了现有的Camshift算法Continuousl y Adaptive eanshift中跟踪目标特征提取精确度低和计算复杂度高的缺陷-Dissertation moving object tracking methods include Kalman filt
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This paper presents a clustering approach
which estimates the specific subspace and the intrinsic dimension of each class. Our approach
adapts the Gaussian mixture model framework to high-dimensional data and estimates
the parameters which best
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一种基于肤色分割、区域分析和模板分布的彩色图像人脸检测算法.首先对输入的彩色图像利用混合高斯模型和亮度模型进行分割,然后根据人脸五官的结构特征对得到的区域进一步分析处理,获得所有可能的候选人脸.接着构造了一种基于双眼和人脸模板的概率模型并利用其对候选人脸进行最终检测.-Based on skin color segmentation, regional analysis and the template in color images of face detection algorithm. F
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Speaker recognition is the task of validating individual s identity using invariant features extracted from their voices print. Speaker recognition technology common applications include authentication, surveillance and forensic applications. This Pa
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文章展示了基于高斯混合模型的语音频谱预测方法。频谱预测可能在传包过程中预防丢包这方面起到大作用。期望最大化算法用两倍或三倍的连续语音因素来测试模型。模型被用来设计第一，儿等指令预测量。预测表用频谱分配状态来估计并和一个简单的参考模型对比。最好的预测表得到一个平均频率扭曲值是0.46dB小于参考模型-This paper presents methods for speech spectrum prediction based
on Gaussian mixture models. Spec
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SUMMARY:
The Algorithms such as SVD, Eigen decomposition, Gaussian Mixture Model, HMM etc. are scattered in different fields. There is the need to collect all such algorithms for quick reference. Also there is the need to view such algorithms in ap
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该系统能够识别连续说出的数字串和若干组姓名。建模是针对子词(sub-word, eg. 音
素)，具有一定的可扩充性。当加入一个新名字时，只需修改发音词典和任务语法即可。模
型为连续混合高斯输出，运用语音决策树聚类形成的绑定状态式三音素。-The system is able to recognize continuously spoken digit string and the number of groups name. Modeling is a sub-word (sub-wo
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基于混合高斯模型的算法，我们可以利用该算法提取前景，检测背景！-Gaussian mixture model-based algorithm, we can take advantage of the the algorithm extracted prospects, detect background!
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This introduction to the expectation–maximization (EM) algorithm
provides an intuitive and mathematically rigorous understanding of
EM. Two of the most popular applications of EM are described in
detail: estimating Gaussian mixture models (GMMs),
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文章通过设计战场电视侦察系统的智能视频处理模块，提高了战场电视侦察系统的工作效率和智能化水平。首先
分析对重要军事目标进行监控的特点，归纳运动目标的特征，根据特征建立正常模型；然后运用中值滤波对监控视频进行
预处理，再采用基于高斯混合模型的背景减除法提取运动目标，通过特征提取确定运动目标的属性，与正常模型进行匹配
处理后，得出运动目标是否异常；最后达成敌重要目标有异常出现时自动告警的目的-Abstract：This article designs the intelligent vi
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本文提供了利用高斯混合模型进行短时交通预测的算法描述，同时对于该算法的性能进行了评价。-This article provides a Gaussian mixture model for short-term traffic forecast algorithm descr iption, were evaluated for the performance of the algorithm.
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研究了基于混合高斯模型的运动目标检测技术,在分析了混合高斯模型的基本原理的基础上,使用了一种
改进的混合高斯模型更新算法
-Studied based on Gaussian mixture model of moving target detection technology, the analysis of the basic principles of Gaussian mixture model based on the use of an improved algorithm
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matlab上对于高斯混合模型的应用，对于图像做出处理的效果-For a Gaussian mixture model matlab on the application of the effect of the image to make a deal
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opencv关于高斯混合模型的说明，可以应用在图像匹配等的领域，为图像处理提供很大方便。-Opencv on gaussian mixture model that can be applied in the field of image matching, etc, provides great convenience for image processing.
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针对扩展目标的高斯混合PHD滤波算法的论文-presents a Gaussian-mixture implementation
of the PHD filter for tracking extended targets
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着重研究了基于高斯混合
模型（GMM, Gaussian Mixture Model)的运动目标检测算法
-Focuses on the Gaussian mixture model-based (GMM, Gaussian Mixture Model) of the moving target detection algorithm
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研究表明超高斯分布更加贴近语音信号的实际分布，然而语音信号很难用单一的概率密度
函数准确描述，针对这一情况，提出了一种用超高斯混合模型对语音信号幅度谱建模的新方法，并推导了
基于此模型的幅度谱最小均方误差估的估计式。仿真结果表明：与传统的短时谱估计算法相比，该算法不
仅能够进一步提高增强语音的信噪比，而且可以有效减小增强语音的失真度，提高增强语音的主观感知
质量。 -Recent research indicates that the speech spectral ampli
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