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Kohonenneural network library is a set of classes and functions for design, train and use Kohonen network (self organizing map) which is one of AI algorithms and useful tool for data mining and discovery knowledge in data (http://knnl.sf.net).
It's a "Hello World" implementation of SOM (Self-Organizing Map) of Teuvo Kohonen, otherwise called as the Kohonen map or Kohonen artificial neural networks.
Discover and manage administrator, service, and web app passwords, keys, and identities. Automate management with approval workflows. Centrally control, audit, monitor, and record all access to critical IT assets.
Hello, This project is the result of my work on the artificial neural network. In the futur is implement Kohonen Network, Multi-Layer Network and Hopfield Network.
OpenNeuron is a neural networks implementation written in Java. Currently supports only Kohonen Network model, but API is designed to be easily extended to model other network types. This implementation was used for face thermal pictures recognition.
Java KohonenNeural Network Library
Kohonenneural network library is a set of classes and functions for design, train and use Kohonen network (self organizing map).
Do you want a neural network OO class?
With documentation?
Do not go further... You found it!
you have here a complete library of different neural network in an OO encapsulation.
Starting from adaline, back propagation, Kohonen
Sign In App is a modern, enjoyable way to sign in visitors and staff, and book desks and meeting rooms.
Our visitor management system streamlines registration, check-in, and authorization processes, while our facility management tools streamline room booking, resource allocation, and asset management. We prioritize security with our advanced risk mitigation measures, including health and safety protocols, emergency messaging, and robust analytics for thorough auditing.
This library implements self-organizing neural networks, also called Kohonen Nets. They can be used for high dimensional data analysis. Example: content based image recognition ( CBIR ).
Net.py is a tool for learning about neural nets. Currently, it only allows the user to experiment with a Hopfield net. I am now extending it to cover the Kohonen net. I'd be pleased to receive suggestions and criticism.