Accord.NET is a .NET machine learning framework. It is combined with scientific computing, audio and image processing libraries. It is written in C# programming language. It is built to extend the capabilities and features of AForge.NET. Later merged together as Accord.NET.
It is a comprehensive framework for creating production-grade computer vision, computer audition, signal processing, machine learning, mathematics, statistics and other computing techniques. It can also be used commercially.
Accord.NET's libraries are:
Scientific Computing libraries
Accord.Math
Accord.Statistics
Accord.MachineLearning
Accord.Neuro
Signal and Image Processing libraries
Accord.Imaging
Accord.Audio
Accord.Vision
Support Libraries
Accord.Controls
Accord.Controls.Imaging
Accord.Controls.Audio
Accord.Controls.Vision
Accord.NET is applicable on Microsoft Windows, Xamarin, Unity3D, Windows Store applications, Linux or mobile.
Ceazar Roberto de Souza created Accord.NET and developing it along with other collaborators.
Timeline
Funding Rounds
Products
Acquisitions
SBIR/STTR Awards
Patents
Further Resources
A Tutorial on Principal Component Analysis with the Accord.NET Framework
César Roberto de Souza
Academic paper
Procedural Generation of Videos to Train Deep Action Recognition Networks
César Roberto de Souza, Adrien Gaidon, Yohann Cabon and Antonio Manuel López Peña
Academic paper
