mixture model

In real-time platform, the Gaussian mixture model (GMM) with the calculation of the effectiveness and easy to realize benefits.

Gaussian mixture model(GMM) has been widely used for text-independent speaker recognition. This method has simple and efficient character.

Gaussian mixture model is firstly built as the statistical model for the intensity image, with an estimation of index number using MDL.

This paper starts around the construction of Gauss Mixture Model (GMM) speaker recognition system.

Finally, use Gaussian mixture model to determine the region whether it's hair region or not.

Gaussian Mixture Model assumes the independence between data while Hidden Markov Model allows Markov assumption in a data series.

Then discuss the actual heterogeneous two-phase oil-water mixture model of coaxial cavity sensor measurement accuracy of the impact.

The initial background is established using the traditional Gaussian mixture model with a global learning rate.

A multi-step clustering algorithm with transformation-based and diagonal-covariance Gaussian mixture model (GMM) is advanced.

Firstly, we introduce the theory of finite mixture model and EM algorithm for maximum likelihood estimation.

This paper introduced three skin-color detecting model: Statistical Color Model, Chroma Space Model and Gaussian Mixture Model.

So the enthalpy must be calculated by the real mixture model when analyzing the humidifier of HAT cycle.

The effect of Gaussian Mixture Model used in training background model is good, but its convergence velocity is low.

Gaussians mixture model (GMM) has been widely used for moving object detection based on background modeling.

This paper presents an unsupervised algorithm for learning a finite mixture model from multivariate data.

We use the fixed-arithmetician DSP chip ( chipboard ) in the DSP, the algorithm of recognition is Gaussian mixture model.

Then, built the color model for background and foreground utilizing the GMM (Gaussian mixture model).

A mixture model to simulate the two dimensional velocity field of the gas liquid two phase flow on sieve plate is presented.

Firstly, a mixture model of image was proposed, and the method of motion segmentation based this model were suggested.

Based on finite Gaussian mixture model of the EM algorithm source code, which has run reports and experimental results.

We put forward a classifying algorithm for compositional data based on finite mixture model with Dirichlet distribution.

This paper sets up a new Support Vector Machine-Gussian Mixture Model(SVM-GMM) to improve speaker recognition rate based on open-set.

The three Frames subtraction and the background subtraction of Gaussian mixture model are researched.

Gaussian mixture model (GMM) is first trained for grass pixel, the grass distribution is then computed based on the trained GMM.

This mixture model is based on the Dirichlet distribution, which offers high flexibility for modeling data.

This paper proposed an improved moving objects detection method based on Gaussian mixture model.

A Gaussian Mixture Model based on color feature is adopted in static layer.

On the Residual Term in the Linear Mixture Model and Its Dependence on the Point Spread Function

Algorithm EM and Its Initialization in Gaussian-Mixture-Model Based Clustering

Probability Density Function Approximation Using Gaussian Mixture Model

Study of Gaussian mixture model for image wavelet coefficients

Modified Linear Mixture Model Applied to theHyperspectral Unmixing Simulation

Finite Mixture Model and Its EM Clustering Algorithm for Remote Sensing Data

Discussions of A Model Selection Method in Time-Series Mixture Model

Study on "Mixture Model" of Overland Braided Stream with Quasi-Two Dimension and One Dimension Unsteady Flow

The Finite Mixture Model and Its EM Algorithm for Line-Type Image Patterns

D-optimal design of a linear log quotient mixture model

MRI Segmentation via Active Contour Model Improved with Gaussian Mixture Model

Research on grassland degradation using spectral mixture model

Study of image denoising based on gaussian mixture model in wavelet domain and median filter

likelihood ratio test of a class of mixture model

Speech Separation Based on Gaussian Mixture Model Probability Density Function Estimation

Motion Segmentation via On-line Gaussian Mixture Model and Texture

Estimation and Testing for Competing Risks Mixture Model

A New Parameter Estimation Algorithm of Gaussian Mixture Model

Multiple region parallel region growing for image segmentation based on Gaussian-mixture model

Speaker Identification Based on Classify Feature Sub-space Gaussian Mixture Model and Neural Net Fusion

A Study of EM Learning Algorithm Based on Gaussian Mixture Model

Gaussian mixture model training method based on genetic algorithms and fuzzy approach

An Approach for Estimating Parameters in Gaussian Mixture Model Based on Maximum Cross Entropy

MR Image Segmentation of Left Ventricle Based on the Multi-information Gaussian Mixture Model

TWS Tracking Techniques Based on Adaptive Gaussian Mixture Model in Phased Array Radar

A Mixture Model With Bathtub Shaped Failure Rate

Image denoising method based on adaptive Gaussian mixture model in wavelet domain

Textured Image Segmentation Based on Gauss Markov Random Field Mixture Model

An unsupervised rough clustering method based on gaussian mixture model

Image Stabilization Based on Adaptive Gaussian Mixture Model

New linear discriminant analysis based on Gaussian mixture model

A Range Image Segmentation Algorithm Based on Gaussian Mixture Model

Speaker recognition system based on Gaussian mixture model

On the effect of variable end member spectra in the linear mixture model

Video Object Segmentation Based on Gaussian Mixture Model

SAR Speckle Reduction Based on Multi-Scale Wavelets and Gauss Mixture Model

Method of Image Denoising Based on Statistical Mixture Model in Wavelet Domain

Regional Color Transfer Based on Gaussian Mixture Model

Parameter Estimation of Mixture Model Based on EM Algorithm

SAR images despeckling based on wavelet and hidden Markov mixture model

Multi-Engine Fusion Based on Mixture Model