The Joone's framework is built with a modular architecture: the 'core engine' is separated from the visual interface and permits easily to implement any new application based on it.
Joone is portable, being written in 100% pure Java. It can run in any environment, from big multiprocessor machines to small palmtop devices.
Neural Network's usability and transportation
The neural networks based on Joone are usable stand-alone (separated from the framework that has created or trained them).
The Joone's based neural networks can be transported using common protocols (like http or ftp) to run on remote machines
The framework is expandable with more components to implement new learning algorithms or new architectures.
With Joone it's possible to implement any kind of optimization; there are two main methods to find the best solution to a given problem (i.e. to find the best neural network): local optimization and global optimization techniques. The local optimization is obtained applying some 'internal' mechanism (the most famous is the momentum), the global optimization, instead, try to find the best solution applying some external technique to select the best performing NN among a predefined group of NNs (like genetic algorithms). Both are implemented with Joone, and many new optimization techniques can be experimented thanks to its expansibility.
Multithreading and scalability
Joone's core engine is based on a multithreaded engine, capable to scale using all the computing resources available.
Joone provides the professional users with a distributed environment to train many neural networks in parallel on several machines.
Joone is freely usable. Its license is the Lesser General Public License (LGPL).
You're encouraged to try it and use it for whatever (both commercial and academic) application!