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'''JOONE''' (Java Object Oriented Neural Engine) is a component based [[neural network]] framework built in [[Java programming language|Java]].
'''JOONE''' (Java Object Oriented Neural Engine) is a component based [[neural network]] framework built in [[Java programming language|Java]].


'''[[Joone (Director)|Joone]] is also the name of a [[pornographic film]] [[director]]/[[producer]].
'''[[Joone''' (Director)|Joone]] is also the name of a [[pornographic film]] [[director]]/[[producer]].


==Features==
==Features==

Revision as of 06:11, 15 January 2007

Java Object Oriented Neural Engine
Developer(s)The Joone Team
Operating systemCross-platform
TypeNeural network software
LicenseFree, Open Source
WebsiteJOONE homepage

JOONE (Java Object Oriented Neural Engine) is a component based neural network framework built in Java.

Joone is also the name of a pornographic film director/producer.

Features

Joone consists of a component-based architecture based on linkable components that can be extended to build new learning algorithms and neural networks architectures.

Components are plug-in code modules that are linked to produce an information flow. New components can be added and reused. Beyond simulation, Joone also has to some extent multi-platform deployment capabilities.

Joone has a GUI Editor to graphically create and test any neural network, and a distributed training environment that allows for neural networks to be trained on multiple remote machines.

Comparison

As of 2006, Joone is the only free component based neural network development environment available. Unlike the two other (commercial) systems that are in existence, Synapse and NeuroSolutions, it is written in Java and has direct cross-platform support. A limited number of components exist and the graphical development environment is rudimentary so it has significantly fewer features than its commercial counterparts.

Joone can be considered to be more of a neural network framework than a full integrated development environment. Unlike its commercial counterparts, it has a strong focus on code-based development of neural networks rather than visual construction.

While in theory Joone can be used to construct a wider array of adaptive systems (including those with non-adaptive elements), its focus is on backpropagation based neural networks.

See also

External links