OpenCog Brainwave | The latest developments in building an open-source mind Orange – Data Mining Fruitful & Fun Image Recognition with Neural Networks Neural networks are one technique which can be used for image recognition. This tutorial will show you how to use multi layer perceptron neural network for image recognition. The Neuroph has built in support for image recognition, and specialised wizard for training image recognition neural networks. Simple image recognition library can be found in org.neuroph.contrib.imgrec package, while image recognitionwizard in Neuroph Studio canis located in [Main Menu > File > New > Image recognition neural network] This tutorial will explain the following: 1. This tutorial is for Neuroph v2.6. 1. Every image can be represented as two-dimensional array, where every element of that array contains color information for one pixel. Picture 1. Each color can be represented as a combination of three basic color components: red, green and blue. Picture 2. int [][] redValues int [][] greenValues int [][] blueValues For example, if pixel at location [20, 10] has color RGB[33, 66, 181] we have Picture 3. 2.
PCL - Point Cloud Library Neural Networks on the NetBeans Platform by Zoran Sevarac Published February 2011 Downloads: : NetBeans Platform Introduction The NetBeans Platform is a generic Java Swing application framework that provides GUI components and a module system for the development of custom desktop applications. Neuroph Studio is a Java neural network development environment built on top of the NetBeans Platform and Neuroph Framework. In addition to providing easy-to-use neural network wizards and tools, Neuroph Studio also integrates basic Java development modules from the NetBeans IDE, so developers can create, test, and deploy various Java components based on neural networks in the same environment. Neural networks are artificial intelligence (machine learning technology) suitable for ill-defined problems, such as recognition, prediction, classification, and control. Brief Overview of Neural Networks with Neuroph Studio Neural networks are computational models inspired by the way the human brain works. Basic Neuron Sample 1. Figure 1. Figure 2. 2.
The SHOGUN Machine Learning Toolbox Documentation We use Doxygen for both user and developer documentation which may be read online here. More than 600 documented examples for the interfaces python_modular, octave_modular, r_modular, static python, static matlab and octave, static r, static command line and C++ libshogun developer interface can be found in the online documentation. In addition, examples are shipped in the examples/(un)documented/[interface] directory in the source code (where interface is one of r_static, octave_static, matlab_static, python, python_modular, r_modular, octave_modular, cmdline, libshogun). Here you may find links to the older, current (latest release) and latest (cutting edge code in github) versions of the documentation: Note that documentation for python-modular is most complete and also that python's help function will show the documentation when working interactively:
Neural network software | Reviews downloads Sharky Neural Network software from SharkTime Sunday,June 06 ,2010 Today I received an Email from software developer of SharkTime.com, and as hundreds of emails I receive daily; I finally receive something worthy to share with my readers. This is Sharky Neural Network, software that allows you to play with neural network development.... Read more XML based neural network processing language While surfing the Internet I found an interesting utility: A Neural network trainer based on XML. NeuroXL Classifier neural network software Monday,June 07 ,2010 Regarding to data organization, a good classification is always needed.
Video: Introducing Gephi 0.7 Introducing Gephi 0.7 from gephi on Vimeo. This is a “madness” screencast overview of brand new Gephi 0.7. Turn on the sound, go on Vimeo to see it in HD, and enjoy! The video highlights the following features: Video License: Creative Commons By-NC-SA Music Credits: Feather Drug – Mysteries – Album Beta test V0.1 Related Posts: Demo Functionality ~ 0.7 video Trackback