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- Description:
Accord.NET Framework is a C# framework which extends the excellent AForge.NET Framework with new tools and libraries.
The framework is comprised by libraries and sample applications demonstrating their features. Some of the libraries include:
- Accord.Math - General math and matrix library with numerical decompositions and related linear algebra methods, such as Nonnegative Matrix Factorization, generalized Eigenvalue and others;
- Accord.Statistics - library with statistical analysis and related tools, such as (Kernel) component and discriminant analysis, partial least squares and hidden Markov models;
- Accord.Imaging - extension to the AForge.NET Imaging library with new filters and routines;
- Accord.Neuro - extension to the AForge.NET Neuro library with new algorithms such as Levenberg-Marquardt with Bayesian regularization and Nguyen-Widrow weight initialization;
- Accord.MachineLearning - extension to AForge's machine learning library with SVMs, K-Means and GMM clustering and related techniques;
- Accord.Vision - extension to the AForge.NET Vision library with realtime object detectors and trackers such as Viola-Jones and Camshift;
- Accord.Audio - experimental library with filters and audio processing routines.
For a complete listing of framework features, please see the feature list at http://accord-net.origo.ethz.ch/wiki/features
- Changes to previous version:
- Adding support for more Haar cascade classifier definitions;
- Optimizing Levenberg-Marquardt learning algorithm;
And several other bugfixes and enhancements. For a complete list of changes, please see the full release notes at http://accord-net.origo.ethz.ch/download/2312
- BibTeX Entry: Download
- Supported Operating Systems: Linux, Windows
- Data Formats: Agnostic
- Tags: Svm, Kernel Methods, Algorithms, Classifiers, Statistics, Clustering Algorithm, Probability Estimation, Discriminant Analysis, Wavelet Transform, Principal Component Analysis, Algebra, Fourier Transfo
- Archive: download here
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