Projects / bnns

bnns

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 (MLP) on tasks that have a 2D character. Tasks include the famous two-spirals task or classification of satellite image data.

Tags	Artificial Neural Networks Visualization Interactive
Licenses	GPLv3
Operating Systems	Linux (32 and 64 bit) BSD
Implementation	C Perl X11 libs only
Translations	English

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Recent releases

2.0.beta5

11 Feb 2013 02:32

Release Notes: This maintenance release adds support for gcc versions above 4.4, uses a default position for the extrapolation window to avoid a deadlock in XCB-enabled Xlib reported on Ubuntu 12.04.1 LTS, drops an obsolete xpm.h include causing compilation errors because libxpm presence was not checked by the configure script, changes interpretation of the --scale-factor value, and introduces a set of supported values.

2.0.beta4

12 Jun 2012 21:54

Release Notes: This beta was focused on refactoring and usability. The command line option sets in Perl scripts that assist in pattern preparation were extended. All control variables have corresponding command line options to make the pattern preparation process comfortable and user friendly. A new interaction feature is included: Freezing and unfreezing of weights coming into a neuron via the Space key at the corresponding RFP. The RFP becomes highlighted to inform users of weights being frozen. Positioning of performance analysis tools was improved.

2.0.beta3

01 Jun 2012 21:59

Release Notes: This release disables user interaction during the training process to improve overall stability, extends the set of commandline options and extends the main menu to include previously unstable options, implements an error-energy preview, improves the Perl scripts which assist pattern preparation, and improves the manual draft.