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» Optimizing number of hidden neurons in neural networks
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ESANN
2006
13 years 9 months ago
Visual object classification by sparse convolutional neural networks
Abstract. A convolutional network architecture termed sparse convolutional neural network (SCNN) is proposed and tested on a real-world classification task (car classification). In...
Alexander Gepperth
GECCO
2010
Springer
152views Optimization» more  GECCO 2010»
14 years 20 days ago
Importing the computational neuroscience toolbox into neuro-evolution-application to basal ganglia
Neuro-evolution and computational neuroscience are two scientific domains that produce surprisingly different artificial neural networks. Inspired by the “toolbox” used by ...
Jean-Baptiste Mouret, Stéphane Doncieux, Be...
BIOADIT
2006
Springer
13 years 11 months ago
Attractor Memory with Self-organizing Input
We propose a neural network based autoassociative memory system for unsupervised learning. This system is intended to be an example of how a general information processing architec...
Christopher Johansson, Anders Lansner
GECCO
2007
Springer
182views Optimization» more  GECCO 2007»
14 years 2 months ago
Generating large-scale neural networks through discovering geometric regularities
Connectivity patterns in biological brains exhibit many repeating motifs. This repetition mirrors inherent geometric regularities in the physical world. For example, stimuli that ...
Jason Gauci, Kenneth O. Stanley
ARC
2009
Springer
175views Hardware» more  ARC 2009»
14 years 2 months ago
A Hardware Accelerated Simulation Environment for Spiking Neural Networks
Spiking Neural Networks (SNNs) model the biological functions of the human brain enabling neuro/computer scientists to investigate how arrays of neurons can be used to solve comput...
Brendan P. Glackin, Jim Harkin, T. Martin McGinnit...