搜索资源列表
Untitled
- 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
GMM_Skin_Detector
- Matlab skin detector。运用高斯混合模型训练的到人的皮肤颜色分布。用于皮肤和人脸检测。-A collection of Matlab scr ipts
gmm_test1
- 使用高斯混合模型（GMM)模拟模式识别的源代码-The use of Gaussian mixture model (GMM) Analog Pattern Recognition of the source code
e_m_matlab
- 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
gaussmix(Bouman)M
- 高斯混合模型用于聚类的程序。可以直接使用。里面有3个例子。-Gaussian mixture model for the clustering process. Can be used directly. Inside there are three examples.
gmm
- 求高斯混合模型的EM算法，matlab程序。-Seeking EM algorithm for Gaussian mixture model, matlab program.
GMM_background_src
- 基于有限混合高斯模型的数据分类 1、使用基于有限高斯混合模型的EM算法对数据样本进行归类 2、使用C++或者Matlab语言编程环境实现该算法，并用给定的数据包对算法的正确性进行检验 -Gaussian mixture model based on limited data classification 1, using the finite Gaussian mixture model based on EM algorithm to classify the data sam
mixtureGussian_jp
- 一种用于图像超分辨率分析的混合高斯模型算法。可实现图像方法，同时保持很好的图像边缘。-For image super-resolution algorithm for Gaussian mixture model analysis. Image method can be realized while maintaining a good edge.
GMM
- 高斯混合模型，有详细的说明，而且有程序,希望下载，很有帮助的！-GMM including explanation and programs
motion3
- 基于混合高斯模型的多目标跟踪算法，对背景图像建立混合高斯模型，实时更新高斯模型，达到更新背景的目的。-Gaussian mixture model-based multi-target tracking algorithm, Gaussian mixture model to establish the background image, real-time updates Gaussian model, to achieve the purpose of updating the backgr
mixture_of_gaussians
- 这个程序是基于混合高斯背景模型的运动目标检测算法，m文件和所用视频放到matlab的工作目录下即可运行-This program is based on the Gaussian mixture background model of moving target detection algorithm, m, and used video files into matlab working directory to run
mixture-Gauss-model-EM-matlab
- EM算法计算混合高斯模型，可以计算三个参数。-Gaussian mixture model EM algorithm, three parameters can be calculated.
EM
- 利用Matlab编程验证用EM算法估计的高斯混合模型的相关参数的性能。-Validate the use of Matlab programming estimated using EM algorithm for Gaussian mixture model parameters related to the performance.
GMM
- 无监督混合高斯模型（GMM）的EM估计，含两篇IEEE论文的源码-This is a set of MATLAB m-files implementing the mixture fitting algorithm described in the paper M. Figueiredo and A.K.Jain, "Unsupervised learning of finite mixture models", IEEE Transaction on Pattern Analys
mixture_of_gaussians
- 完整的混合高斯模型，能够很好的尽力背景模型-Complete Gaussian mixture model, very good to try to background model
guass
- matlab中可以运行的混合高斯模型，用于运动检测，提供了一个基本的程序框架，各种改进算法可以基于本程序进行-matlab can run Gaussian mixture model for motion detection, provides a basic framework of the program, various improvements to the algorithm based on the Program.
clustering
- 使用K-means，混合高斯模型（GMM），层次聚类算法实现的多类别数据的聚类。内含详细的实验报告。-Using K-means, Gaussian mixture model (GMM), hierarchical clustering algorithm to achieve multi-class data clustering. Including a detailed lab report.
fruit-recognition
- 水果分类 fruit recognition 运行demo即可 这个程序主要是通过对训练样本中的三幅图像提取的颜色信息建立混合高斯模型，然后对目标图像进行测试。 在demo最后一段中，可以替换‘t1.jpg’，以便进行不同图片的识别。 程序运行过程比较慢，请耐心等待。 运行结果是蓝色点聚集的区域是属于橘子的。- fruit recognition
EM_GMM
- 用EM算法对混合高斯模型中的参数进行估计 一种改进的EM算法即Monte Carlo EM算法（MCEM）的一个简单例子(The parameters in the mixed Gaussian model are estimated by EM algorithm An improved EM algorithm is a simple example of the Monte Carlo EM algorithm (MCEM))
EM算法用于高斯混合模型
- EM算法在高斯混合模型的参数估计中的应用，内服Matlab程序例子。(Application of Matlab program and EM algorithm in parameter estimation of Gaussian mixture model.)