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» Design of Neural Networks
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WAPCV
2004
Springer
15 years 10 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
ICANN
2010
Springer
15 years 4 months ago
Deep Bottleneck Classifiers in Supervised Dimension Reduction
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...
Elina Parviainen
IJCINI
2008
107views more  IJCINI 2008»
15 years 4 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
130
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ECAL
2007
Springer
15 years 10 months ago
Developmental Neural Heterogeneity Through Coarse-Coding Regulation
Abstract. A coarse-coding regulatory model that facilitates neural heterogeneity through a morphogenetic process is presented. The model demonstrates cellular and tissue extensibil...
Jekanthan Thangavelautham, Gabriele M. T. D'Eleute...
155
Voted
ISNN
2005
Springer
15 years 10 months ago
Feature Selection and Intrusion Detection Using Hybrid Flexible Neural Tree
Current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (if anything)...
Yuehui Chen, Ajith Abraham, Ju Yang