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2dlidarobstacledetection

Obstacle Detection using Hokuyo 2D Lidar

3dunderworld-structured-light-scanner

[3DUNDERWORLD-SLS] High-accuracy Structured-Light Scanner.

3pre

matlab code for doing visual SLAM for RGBD SLAM

background-subtraction-using-gmm

This project is the C++ implementation of Background Subtraction using adaptive GMM models as discussed by Zoran Zivkovic in his paper "Improved Adaptive Gaussian Mixture Model for Background Subtraction".

bayes

贝叶斯过滤垃圾评论

classification

感知器、贝叶斯分类、决策树分类、K最近邻法、逻辑回归、支持向量机...

classifier

基础分类器算法实现。包括朴素贝叶斯等

courseradownloader

A python tool used for download coursera's videos and subtitles.

cppgaussionelemination

Perform Gaussion elemination with Cpp

cvpr

Computer Vision and Pattern Recognition

cvpr-1

This is my code used for pedestrian recognition.

cvpr2014

Code for "Efficient feature extraction, aggregation and classification for action recognition" (Kantorov, Laptev, CVPR'14)

demo_obstacle_avoidance

A simple obstacle avoidance demo using a LIDAR sensor

fast-gmm

a Gaussian Mixture Model (GMM) implementation.

fgm

Factorized Graph Matching for CVPR 2012, CVPR 2013

geyser_temp_analysis

Determining geyser eruption times from temperature sensor data

gmm

Gaussian Mixture Models in Python

gmm-1

Gaussian Mixture Model Estimator using Expectation Maximization

gmm-2

Gaussian Mixture Model for Audio Classification

gmm-3

Gaussian Mixture Model estimation

gmm-clutering

Gaussian Mixture Model clustering using OpenCv Expectation Maximization implementation

gmmreg

Implementations of the robust point set registration algorithm described in the paper "Robust Point Set Registration Using Gaussian Mixture Models", Bing Jian and Baba C. Vemuri, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(8), pp. 1633-1645.

gpsdinspector

Maps and GPS data

grabcut

NOTE: This work was never completed - the status is unknown. Image segmentation using GMM EM and Graph Cuts

graph_cut

graphcut

GraphCut

hmm

This project is a Ruby gem ('hmm') for machine learning that natively implements a (somewhat) generalized Hidden Markov Model classifier. At present, it is capable of supervised learning (using labeled training data) and Viterbi decoding. Unsupervised learning is on the way.

hmm-1

Hidden Markov models in Python

hmm-2

hidden markov model on GPU

hmm-3

Pure python implementation of an HMM with standard inference algorithms