搜索资源列表
Classification
- 分类器程序，混合高斯分类器，用于语音图像的分类处理-classifier procedures, Gaussian mixture classifier for the classification of voice processing images
fit_mix_gaussian
- 混合高斯模型的曲线拟合matlab源代码-Gaussian mixture model of curve fitting Matlab source code
MixGaussDemo
- 人体运动跟踪 混合高斯模型＋GRISON方法-human motion tracking GMM + GRISON methods
backmode824
- 这个是应用混合高斯的背景建模的方法进行的目标检测的程序,需要应用opencv.供大家交流交流-this is the application of Gaussian mixture of the background modeling method for the detection procedures, opencv needed. for the exchange of exchange
EM_GM
- 混合高斯分布EM算法，可以算混合高斯分布的三个参数。混合高斯分布更接近系数分布。-mixed Gaussian distribution EM algorithm can calculate mixed Gaussian distribution of the three parameters. Mixed closer to the Gaussian distribution coefficient.
EM_TuXiangfenge
- 期望最大EM算法及其在混合高斯模型中的应用.caj
fc5j_EM_matlab
- em算法求解混合高斯模型，适合图像处理中，对象分割-em algorithm Gaussian mixture model suitable for image processing, object segmentation
82603023mixture_of_gaussians
- 高斯混合噪声程序, 程序完整可以直接使用很方便(this is a matlab gmm program, easy and good)
EM_GM_fast
- 高斯混合模型中的EM算法（就不完整数据的极大似然估计）应用(EM algorithm in Gauss mixture model)
GMM
- 此算法实现高斯混合，可以对初始聚类算法选择c均值和EM，可以实现密度估计和分类。(This GMM algorithm can estimate the density and class, the initial steps can select the C-mean and EM.)
GMM
- 高斯混合聚类的python实现代码，里面有data的demo(Python implementation code of Gauss mixed clustering)
gmm
- 基于高斯混合模型的运动目标检测，opencv平台，直接可用(Moving target detection of Gauss mixed model)
GMMs
- function对数据EM算法进行fit，并对产生的高斯混合模型的最大似然估计进行绘图。输出结构体obj，带有高斯混合模型的参数mu，sigma。(Function carries out fit for data EM algorithm, and draws the maximum likelihood estimation of the Gauss mixture model. The output structure is obj, with the parameter mu and s
GMM
- 实现了EM算法对高斯混合模型进行聚类，并将聚类结果用图像展示出来，希望对混合模型的朋友有用。(The EM algorithm is implemented to cluster the Gauss mixture model, and the clustering results are displayed with images, hoping to be useful to friends of the mixed models.)
RCY-GMMtest1
- 高斯混合模型（GMM,Gaussian Mixture Model）参数如何确立这个问题，详细讲解期望最大化（EM,Expectation Maximization）算法的实施过程。(How to establish the parameters of Gauss mixture model and explain the implementation process of the expectation maximization algorithm in detail.)
GMM_test1
- 高斯混合模型的前景提取代码，本人测试可用。(Gauss mixture model of the foreground extraction code)
Experient4
- 利用opencv高斯混合背景建模，并进行开闭运算滤波， 提取视频监控中的车辆(Using opencv Gaussian mixture background modeling and opening and closing operation filtering to extract vehicles in video surveillance)
3-基于高斯混合模型的语音识别
- 基于高斯混合模型的语音识别，有完整的数据集和matlab代码(Speech recognition based on Gaussian mixture model, complete data set and matlab code)
GMM-HMRF
- 基于高斯混合模型和隐马尔科夫模型的图像分割算法(Image segmentation algorithm based on Gaussian mixture model and hidden Markov model)
BIC确定GMM聚类簇数
- 通过贝叶斯信息准则确定高斯混合聚类方法的聚类簇数(Determining the Cluster Number of GMM Clusters by BIC)