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使用voicebox进行说话人识别,初步介绍如何用GMM(Gaussian Mixture Model)的方法来进行说话人辨识(Speaker Identification),并在Matlab下,尝试通过调整参数来提高得分-For speaker recognition using the voicebox, initially describes how to use GMM (Gaussian Mixture Model) approach to speaker recognition (S
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EM算法用于混合高斯模型的参数估计,并附有一个例子进行说明,程序解释-EM algorithm is used for of the gaussian mixture model parameter estimation, and with an example specification, process explanation
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混合高斯模型的C++程序,封装成为C++的类,直接调用即可。-gaussian mixture model
train code
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MATLAB中实现GMM算法的原始代码,实现图像分割-GMM algorithm implemented in MATLAB source code for image segmentation
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基于码书的运动目标检测是和混合高斯模型(MoG,GMM)类似的而简单有效的背景剪除方法,附件是VC++6.0编写的基于码书的运动目标检测,可直接读取摄像头,也可改为读取硬盘视频文件,需安装Opencv1.1-Codebook-based moving target detection and Gaussian mixture model (MoG, GMM) and a similar cut off the background simple and effective method of a
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学习opencv图像处理中人体目标跟踪的一些很有用的资料,主要是讲camshift,meanshift和高斯混合模型。-Learning opencv image-processing for target tracking in the human body a number of very useful information, mainly speaking camshift, meanshift and Gaussian mixture model.
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基于opencv实现的混合高斯背景建模,C++程序-gaussian mixture model for background modeling
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图像的操作,及视频流的相关操作,基于opencv,运动目标检测,中值滤波,高斯背景模型,混合高斯模型-The operation of the image, and video streams related operations, based on the opencv, motion detection, median filtering, Gaussian background model, Gaussian mixture model
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基于EM算法的高斯混合模型参数估计Matlab算法,-EM algorithm-based parameter estimation of Gaussian mixture model
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基于变权重MRF的图像分割算法,特征场是使用混合高斯模型,标记场使用Pott模型,基于迭代条件模式进行分割-MRF based on weighted image segmentation algorithm, feature field is the use of Gaussian mixture model, using the tag field Pott model segmentation based on iterative model conditions
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EM聚类算法,是学习混合高斯模型的好帮手-EM algorithm, Gaussian mixture model to learn a good helper
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基于混合高斯模型的背景建模方法的实现,用C++语言编写-Gaussian mixture model-based background modeling method of implementation, with C++ language
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改进的高斯混合模型用于运动目标的检测和分割,利用C++和matlab混合编程.-Improved Gaussian mixture model for moving object detection and segmentation, the use of C++ and matlab programming mixed.
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实现混合高斯模型的聚类算法 利用最大似然估计和最大期望的方法来实现混合高斯模型-Gaussian mixture model to achieve clustering algorithm using the maximum likelihood estimation and the greatest way to achieve the desired mixed-Gaussian model
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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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一个强大的统计模式识别工具箱,包含高斯分类器,高斯混合模型,主成分分析,支持向量机等常见分类方法。-A powerful statistical pattern recognition toolbox, including the Gaussian classifier, Gaussian mixture model, principal component analysis, support vector machines and other common classification met
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高斯混合模型的matlab的实现,但是不包含em算法在里面,但是有版权,注意阅读内容-Gaussian mixture model of the matlab implementation, but does not include the em algorithm inside, but has the copyright and pay attention to read the content
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通过em算法实现对数据的高斯混合模型的分类-Em algorithm through implementation of data Gaussian mixture model classification
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高斯混合模型的em
内含源代码与例子和实验报告-Gaussian mixture model of the em algorithm
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The BYY annealing learning algorithm for Gaussian mixture with automated model selection
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