beta

Research tool for interactive training of artificial neural networks.

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Description

BNNS is a research tool for interactive training of artificial neural networks based on the Response Function Plots visualization method. It enables users to simulate, visualize and interact in the learning process of a Multi-Layer Perceptron on tasks which have a 2D character. Tasks like the famous two-spirals task or classification of satellite image data.

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Features

  • Reset of weights connected to a neuron.
  • Freeze/Unfreeze of weights connected to a neuron.
  • Basic support for scaling of RFPs, preview of RFP in its native size.
  • Preview of conflicts between output layer neurons.
  • Preview of error energy on output layer RFPs.
  • Preview of Training/Testing patterns.
  • Sigmoidal/Softmax activation on output layer.
  • Logging of MSE and of the sum of output layer responses.
  • Perl scripts to prepare bnns patterns from PGM data.
  • Perl script to prepare bnns patterns from Boston Remote Sensing Testbed data.
  • Maintained User Manual.

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Additional Project Details

Languages

English

Intended Audience

Science/Research

User Interface

Console/Terminal, X Window System (X11)

Programming Language

C, Perl

Registered

2009-12-18

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