Sciweavers

715 search results - page 36 / 143
» Neural Network with Matrix Inputs
Sort
View
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
14 years 2 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
WCE
2007
13 years 10 months ago
A Neural Network Approach to Objective Evaluation of Seam Pucker
—Seam pucker grade is one of the most important quality parameters in garments manufacturing industry. At present, seam pucker is usually evaluated by human inspectors, which is ...
K. L. Mak, Wei Li
BMVC
1998
13 years 10 months ago
Choosing an Optimal Neural Network Size to aid a Search Through a Large Image Database
In this paper a fast method of selecting a neural network architecture for pattern recognition tasks is presented. We demonstrate that our proposed method of selecting both input ...
Kieron Messer, Josef Kittler
JCNS
1998
134views more  JCNS 1998»
13 years 8 months ago
Analytical and Simulation Results for Stochastic Fitzhugh-Nagumo Neurons and Neural Networks
An analytical approach is presented for determining the response of a neuron or of the activity in a network of connected neurons, represented by systems of nonlinear ordinary stoc...
Henry C. Tuckwell, Roger Rodriguez
RSCTC
2000
Springer
147views Fuzzy Logic» more  RSCTC 2000»
14 years 12 days ago
Towards Rough Neural Computing Based on Rough Membership Functions: Theory and Application
This paper introduces a neural network architecture based on rough sets and rough membership functions. The neurons of such networks instantiate approximate reasoning in assessing ...
James F. Peters, Andrzej Skowron, Liting Han, Shee...