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151
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PRL
2000
182views more  PRL 2000»
15 years 3 months ago
Bayesian MLP neural networks for image analysis
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
Aki Vehtari, Jouko Lampinen
112
Voted
TSMC
2002
80views more  TSMC 2002»
15 years 3 months ago
A feedforward neural network controlling the movement of a 3-DOF finger
This paper describes the dynamic control of a 3 degree of freedom (DOF) finger emulating a human finger for reaching a desired fingertip position in space. The control consists of ...
Emanuele Lindo Secco, Giovanni Magenes
ML
2007
ACM
192views Machine Learning» more  ML 2007»
15 years 3 months ago
Annealing stochastic approximation Monte Carlo algorithm for neural network training
We propose a general-purpose stochastic optimization algorithm, the so-called annealing stochastic approximation Monte Carlo (ASAMC) algorithm, for neural network training. ASAMC c...
Faming Liang
137
Voted
IAJIT
2010
230views more  IAJIT 2010»
15 years 2 months ago
An Unsupervised Artificial Neural Network Method for Satellite Image Segmentation
: Image segmentation is an essential step in image processing. The goal of segmentation is to simplify and/or to change the representation of an image into a form easier to analyze...
Mohamad Awad
145
Voted
MICAI
2010
Springer
15 years 2 months ago
Combining Neural Networks Based on Dempster-Shafer Theory for Classifying Data with Imperfect Labels
This paper addresses the supervised learning in which the class membership of training data are subject to uncertainty. This problem is tackled in the framework of the Dempster-Sha...
Mahdi Tabassian, Reza Ghaderi, Reza Ebrahimpour