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137
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WAPCV
2004
Springer
15 years 9 months ago
Learning of Position-Invariant Object Representation Across Attention Shifts
Abstract. Selective attention shift can help neural networks learn invariance. We describe a method that can produce a network with invariance to changes in visual input caused by ...
Muhua Li, James J. Clark
103
Voted
BC
2006
63views more  BC 2006»
15 years 3 months ago
Dynamic neural field with local inhibition
Abstract A lateral-inhibition type neural field model with restricted connections is presented here and represents an experimental extension of the Continuum Neural Field Theory (C...
Nicolas P. Rougier
149
Voted
IWCMC
2010
ACM
15 years 5 months ago
On the use of random neural networks for traffic matrix estimation in large-scale IP networks
Despite a large body of literature and methods devoted to the Traffic Matrix (TM) estimation problem, the inference of traffic flows volume from aggregated data still represents a ...
Pedro Casas, Sandrine Vaton
IJCINI
2008
107views more  IJCINI 2008»
15 years 3 months ago
Artificial Neural Networks that Classify Musical Chords
An artificial neural network was trained to classify musical chords into four categories--major, dominant seventh, minor, or diminished seventh--independent of musical key. After ...
Vanessa Yaremchuk, Michael R. W. Dawson
118
Voted
EPIA
2003
Springer
15 years 9 months ago
Evolutionary Neuroestimation of Fitness Functions
Abstract. One of the most influential factors in the quality of the solutions found by an evolutionary algorithm is the appropriateness of the fitness function. Specifically in ...
Jesús S. Aguilar-Ruiz, Daniel Mateos, Domin...