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» Boosting in Probabilistic Neural Networks
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ICPR
2004
IEEE
14 years 9 months ago
A Software Algorithm Prototype for Optical Recognition of Embossed Braille
Braille is a tactile format of written communication for sight-impaired people worldwide. This paper proposes a software solution prototype to optically recognise single sided emb...
Lisa Wong, Stephan Hussmann, Waleed H. Abdulla
IJON
2006
132views more  IJON 2006»
13 years 8 months ago
A binary neural decision table classifier
In this paper, we introduce a neural network -based decision table algorithm. We focus on the implementation details of the decision table algorithm when it is constructed using t...
Victoria J. Hodge, Simon O'Keefe, Jim Austin
TNN
2010
171views Management» more  TNN 2010»
13 years 3 months ago
Sensitivity versus accuracy in multiclass problems using memetic Pareto evolutionary neural networks
This paper proposes a multiclassification algorithm using multilayer perceptron neural network models. It tries to boost two conflicting main objectives of multiclassifiers: a high...
Juan Carlos Fernández Caballero, Francisco ...
NN
2006
Springer
13 years 8 months ago
Missing data imputation through GTM as a mixture of t-distributions
The Generative Topographic Mapping (GTM) was originally conceived as a probabilistic alternative to the well-known, neural networkinspired, Self-Organizing Maps. The GTM can also ...
Alfredo Vellido
APIN
1999
107views more  APIN 1999»
13 years 8 months ago
Massively Parallel Probabilistic Reasoning with Boltzmann Machines
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Petri Myllymäki