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[Multimedia Develop] GMM train DL : 0: 用于gmms的训练程序
Update : 2011-04-27 Size : 19.19kb Publisher : liuevan48
[matlab] gmm_utilities DL : 1: 高斯滤波器 matlab toolbox For GMMs and Gaussian kernels-Gaussian filter matlab toolboxFor GMMs and Gaussian kernels
Update : 2025-02-19 Size : 14kb Publisher : onlyjoker
[Books] GMMBooks DL : 0: 3 books about Gaussian Mixture Models Detail: CLustering with GMMs Distance between GMMs Initialize G-3 books about Gaussian Mixture Models Detail: CLustering with GMMs Distance between GMMs Initialize GMM
Update : 2025-02-19 Size : 768kb Publisher : ChipChipKnight
[OpenCV] GMMS DL : 0: OPENCV下基于高斯混合模型的图像分割，程序中还有基于大津法的图像分割和金子塔分割。-OPENCV Based on Gaussian mixture model of image segmentation, the program also includes Otsu method based on image segmentation and the segmentation pyramid.
Update : 2025-02-19 Size : 486kb Publisher : jiaojiao003
[Special Effects] Background.Modeling.using.Mixture.of.Gaussians.for DL : 0: 这篇文章是关于如何改进混合高斯法的一个综述，混合高斯法用于目标检测，目标分割。-This article is an overview of how to improve the GMMS ,the GMMS is used for target detection, object segmentation.
Update : 2025-02-19 Size : 1.25mb Publisher : 黄鹏
[Special Effects] gmms DL : 0: 基于混合高斯模型的目标检测，静止摄像机下的视频序列-Gaussian mixture model-based object detection, static camera video sequence under
Update : 2025-02-19 Size : 21kb Publisher : lei
[Program doc] Gupta-and-Chen---2010---Theory DL : 0: 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), and estimat- ing hidden Markov models (HMMs). EM solutions are also derived for learning an optimal mixture of ﬁ xed models, for estimating the parameters of a compound Dirichlet distribution, and for dis-entangling superimposed signals. Practical issues that arise in the use of EM are discussed, as well as variants of the algorithm that help deal with these challenges.,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), and estimat- ing hidden Markov models (HMMs). EM solutions are also derived for learning an optimal mixture of ﬁ xed models, for estimating the parameters of a compound Dirichlet distribution, and for dis-entangling superimposed signals. Practical issues that arise in the use of EM are discussed, as well as variants of the algorithm that help deal with these challenges.
Update : 2025-02-19 Size : 872kb Publisher : steve
[EditBox] HTK-samples-3 DL : 0: his package contains a set of functions for calling interfacing with HTK from Matlab. Right now its mostly limited to training GMMs and HMMs. It converts your Matlab data into a format that HTK understands and calls HTK command line programs. The path to the HTK binaries is hardcoded in get_htk_path.m-his package contains a set of functions for calling interfacing with HTK from Matlab. Right now its mostly limited to training GMMs and HMMs. It converts your Matlab data into a format that HTK understands and calls HTK command line programs. The path to the HTK binaries is hardcoded in get_htk_path.m
Update : 2025-02-19 Size : 2.26mb Publisher : abdo
[matlab] GMR-multiConstraints-v2.0 DL : 0: Demonstration of the reproduction of a generalized trajectory through Gaussian Mixture Regression (GMR), when considering two independent constraints represented separately in two Gaussian Mixture Models (GMMs). Through regression, a smooth generalized trajectory satisfying the constraints encapsulated in both GMMs is extracted, with associated constraints represented as covariance matrices.
Update : 2025-02-19 Size : 18kb Publisher : student vala
[Speech/Voice recognition/combine] voice-box-GMM DL : 0: 语音处理GMM相关算法,1.计算概率密度并画出高斯混合模型，2.计算边际，条件混合高斯密度,3估计两个GMM模型的Kullback-Leibler divergence。-GMM relating to speech processing algorithms.1,to calculate probability densities from or plot a Gaussian mixture model.2,marginal and conditional Gaussian mixture densities. 3, Kullback-Leibler divergence between two GMMs .
Update : 2025-02-19 Size : 21kb Publisher : 王愈
[Speech/Voice recognition/combine] Gammashirp-filter DL : 0: In this paper, we figure out the use of appended jitter and shimmer speech features for closed set text independent speaker identification system. Jitter and shimmer features are extracted from the fundamental frequency contour and added to baseline spectral features, specifically Mel-frequency Cepstral Coefficients (MFCCs) for human speech and MFCC-GC which integrate the Gammachirp filterbank instead of the Mel scale. Hidden Markov Models (HMMs) with Gaussian Mixture Models (GMMs) state distributions are used for classification. Our approach achieves substantial performance improvement in a speaker identification task compared with a state-of-the-art robust front-end in a clean condition.
Update : 2025-02-19 Size : 250kb Publisher : mansouri
[Special Effects] GMMS DL : 0: 基于高斯混合模型的图像分割程序，结合OpenCV,包括OTSU、金字塔分割、自适应阈值分割-Image segmentation program based on Gaussian mixture model, combined with OpenCV, including OTSU, pyramid segmentation, adaptive thresholding
Update : 2025-02-19 Size : 1.96mb Publisher : user
[AI-NN-PR] gmms DL : 0: matlab中的高斯混合模型代码，机器学习基础学习-Gaussian mixture model matlab code, machine learning based learning
Update : 2025-02-19 Size : 2kb Publisher : 振超张
[matlab] GMMs DL : 0: 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 sigma of Gauss mixture model.)
Update : 2025-02-19 Size : 1kb Publisher : RaymondW
[Mathimatics-Numerical algorithms] GMMs作业 DL : 0: 机器学习作业GMMs算法实现，机器学习课程的一个小作业，没什么用。(Implementation of machine learning task GMMs algorithm)
Update : 2025-02-19 Size : 2kb Publisher : js111