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intro.html
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---
layout: default
title: "Introduction"
comments: false
---
<div id="intro" class="fixed">
<h1>
<a href="http://accord-framework.net">The Accord.NET Image Processing and Machine Learning Framework</a></h1>
<p>
Accord.NET is a framework for scientific computing in .NET. The framework is comprised
of multiple librares encompassing a wide range of scientific computing applications,
such as statistical data processing, machine learning, pattern recognition, including
but not limited to, computer vision and computer audition. The framework offers
a large number of probability distributions, hypothesis tests, kernel functions
and support for most popular performance measurements techniques.
</p>
<h1>
Structural organization</h1>
<p>
The framework is divided in libraries, available either through an executable installer,
standalone compressed archives and <a href="http://nuget.org/packages?q=Accord.NET"
rel="nofollow">NuGet packages</a>. Those libraries include:
</p>
<h2>
Scientific Computing</h2>
<ul>
<li><strong><a href="http://accord-framework.net/docs/html/N_Accord_Math.htm">Accord.Math</a></strong>
Contains a matrix extension library, along with a suite of <a href="http://accord-framework.net/docs/html/N_Accord_Math_Decompositions.htm">
numerical matrix decomposition methods</a>, <a href="http://accord-framework.net/docs/html/N_Accord_Math_Optimization.htm">
numerical optimization algorithms</a> for <a href="http://accord-framework.net/docs/html/T_Accord_Math_Optimization_Cobyla.htm">
constrained</a> and <a href="http://accord-framework.net/docs/html/T_Accord_Math_Optimization_BroydenFletcherGoldfarbShanno.htm">
unconstrained problems</a>, <a href="http://accord-framework.net/docs/html/T_Accord_Math_Special.htm">special functions</a> and other tools for
scientific applications. </li>
<li><strong><a href="http://accord-framework.net/docs/html/N_Accord_Statistics.htm">
Accord.Statistics</a></strong> Probability distributions, statistical models and
methods such as Linear and Logistic regression, Hidden Markov Models, (Hidden) Conditional
Random Fields, Principal Component Analysis, Partial Least Squares, Discriminant
Analysis, Kernel methods and functions and many other related techniques. </li>
<li><strong><a href="http://accord-framework.net/docs/html/N_Accord_MachineLearning.htm">
Accord.MachineLearning</a></strong> Support Vector Machines, Decision Trees, Naive
Bayesian models, K-means, Gaussian Mixture models and general algorithms such as
RANSAC, Cross-validation and Grid-Search for machine-learning applications.
</li>
<li><strong><a href="http://accord-framework.net/docs/html/N_Accord_Neuro.htm">Accord.Neuro</a></strong>
Neural learning algorithms such as <a href="http://accord-framework.net/docs/html/T_Accord_Neuro_Learning_LevenbergMarquardtLearning.htm">Levenberg-Marquardt (LM)</a>,
<a href="http://accord-framework.net/docs/html/T_Accord_Neuro_Learning_ParallelResilientBackpropagationLearning.htm">Parallel Resilient Backpropagation</a>,
Deep learning, <a href="http://accord-framework.net/docs/html/T_Accord_Neuro_Networks_RestrictedBoltzmannMachine.htm">Restricted Boltzmann Machines</a>, initialization procedures such as Nguyen-Widrow
and other neural network related methods. </li>
</ul>
<h2>
Signal and Image Processing</h2>
<ul>
<li><strong><a href="http://accord-framework.net/docs/html/N_Accord_Imaging.htm">Accord.Imaging</a></strong>
Interest point detectors (Harris, SURF and FAST), image matching and image stitching
methods. Can create integral images and other image transformations, plus additional
image filters for image processing a applications. </li>
<li><strong><a href="http://accord-framework.net/docs/html/N_Accord_Audio.htm">Accord.Audio</a></strong>
Process, transforms, filters and handle audio signals for machine learning and statistical
applications. </li>
<li><strong><a href="http://accord-framework.net/docs/html/N_Accord_Vision.htm">Accord.Vision</a></strong>
Real-time face detection and tracking, as well as general methods for detecting,
tracking and transforming objects in image streams. Contains cascade definitions,
Camshift and Dynamic Template Matching trackers. </li>
</ul>
<h2>
Support Libraries</h2>
<ul>
<li><strong>Accord.Controls</strong> Histograms, scatter-plots and tabular data viewers
for scientific applications. </li>
<li><strong>Accord.Controls.Imaging</strong> Windows Forms controls to show and handle
images. Contains a convenient ImageBox control which mimics the traditional MessageBox
behavior for quickly displaying or inspecting images. </li>
<li><strong>Accord.Controls.Audio</strong> Windows Forms controls to display waveforms
and audio-related information. </li>
<li><strong>Accord.Controls.Vision</strong> Windows Forms components and controls to
track head, face and hand movements and other computer vision related tasks.
</li>
</ul>
<h1>
Highlights</h1>
<p>
Some features that might interest you:</p>
<ul>
<li>A <a href="docs/html/T_Accord_Math_Matrix.htm">matrix library based on extension
methods over standard .NET structures</a>, giving room for increased code reuse
and allowing the gradual change of already existing algorithms;</li>
<li>More <a href="http://accord-framework.net/docs/html/N_Accord_Statistics_Distributions.htm">
than 40 different statistical distributions</a> which can be plugged in the most
varying statistical methods, such as Hidden Markov Models and mixture models;</li>
<li>More <a href="http://accord-framework.net/docs/html/N_Accord_Statistics_Testing.htm">
than 30 hypothesis tests</a>, including one-sample, two-sample, multiple-sample
tests, contingency table tests for performance assessment and ANOVA tests;</li>
<li>More <a href="http://accord-framework.net/docs/html/N_Accord_Statistics_Kernels.htm">
than 38 kernel functions</a> ready to be plugged into any of the available kernel
methods, such as Kernel Support Vector Machines, Kernel Principal Components and
Kernel Discriminant Analysis. </li>
</ul>
<h1>
Sample applications
</h1>
<p>
The framework comes with a library of sample applications so you can start writing
code earlier. Applications range from statistics data preprocessing (statistical
analysis, including PCA, KDA, LDA, PLS), image processing (image categorization,
corners detection, image stitching), audio processing (data gathering, blind source
separation), to video processing (depth image analysis with Microsoft's Kinect).
</p>
<p>
Two sample applications are shown below:
</p>
<div class="video">
<iframe src="//www.youtube.com/embed/m7dA86oyJvU?list=PLb8yJtCIm8PQRC0t8re7b5mOCP8s6iBk9"
width="560" height="315" frameborder="0" allowfullscreen="1"></iframe>
<iframe src="//www.youtube.com/embed/tqAfqJsW2Wo?list=PLb8yJtCIm8PQRC0t8re7b5mOCP8s6iBk9"
width="560" height="315" frameborder="0" allowfullscreen="1"></iframe>
</div>
<h1>
Real-world, academical and practical applications</h1>
<p>
Here is a <a href="publications.html">list of published works using the Accord.NET Framework</a>,
including academical publications, hobby and commercial products, research projects
and teaching material.</p>
</div>