Feature reduction projections and classifier models are learned by training dataset and applied to classify testing dataset. A few approaches of feature reduction have been compared in this paper: principle component analysis (PCA), linear discriminant analysis (LDA) and their kernel methods (KPCA,KLDA). Correspondingly, a few approaches of clas…

Image segmentation using the EM algorithm that relies on a GMM for intensities and a MRF model on the labels. Based on "Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm" (Zhang, Y et al.)

Implemented Gaussian Mixture Models (GMM) for image color segmentation.

Color image segmentatiom using several state-of-the-art clustering algorithms, including GMM, FCM, FSC and MEC.

codes for MMPM (TIP2018)

Replication code for simulating and estimation by GMM of DSGE models with higher-order statistics

Gaussian Mixture Model for Clustering

This repositories contains implementation of various Machine Learning Algorithms such as Bayesian Classifier, Principal Component Analysis, Fisher Linear Discriminator, Face Recognition and Reconstruction, Gaussian Mixture Model based Segmentation, Otsu's Segmentation, Neural Network etc. Relevant data sets and results are also included.

EN: Gaussian Mixture Model for Image Segmentation || FR: mélange gaussien pour la segmenation d'image

ESE 650: Learning in Robotics Project 1, Color Segmentation using Gaussian Mixture Models

Machine Learning with MATLAB

基于LabView+MATLAB的说话人识别系统

📈 linear, ridge, logistic regression; k-NN; naive Bayes; SGD; neural networks; PCA; Isomap; k-means; GMM; SVM; CycleGAN

Gaussian mixture model for clustering

Synthetic Data Generation (SDG) by Gaussian Mixture Model (GMM) Distribution

k-means, GMM, linear classifier, mlp

Speaker Recognition based on GMM

Gaussian mixture model for early detection of pattern changes in data streams