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» Two-Dimensional Phase Unwrapping Using Neural Networks
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EOR
2006
73views more  EOR 2006»
13 years 7 months ago
Path relinking and GRG for artificial neural networks
Artificial neural networks (ANN) have been widely used for both classification and prediction. This paper is focused on the prediction problem in which an unknown function is appr...
Abdellah El-Fallahi, Rafael Martí, Leon S. ...
GECCO
2004
Springer
14 years 25 days ago
Shortcomings with Tree-Structured Edge Encodings for Neural Networks
In evolutionary algorithms a common method for encoding neural networks is to use a tree-structured assembly procedure for constructing them. Since node operators have difficulties...
Gregory Hornby
ICDAR
2009
IEEE
14 years 2 months ago
Evaluating Retraining Rules for Semi-Supervised Learning in Neural Network Based Cursive Word Recognition
Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, inc...
Volkmar Frinken, Horst Bunke
ICRA
2007
IEEE
117views Robotics» more  ICRA 2007»
14 years 1 months ago
Predicting Object Dynamics from Visual Images through Active Sensing Experiences
Prediction of dynamic features is an important task for determining the manipulation strategies of an object. This paper presents a technique for predicting dynamics of objects re...
Shun Nishide, Tetsuya Ogata, Jun Tani, Kazunori Ko...
NPL
2006
85views more  NPL 2006»
13 years 7 months ago
A Neural Model for Context-dependent Sequence Learning
A novel neural network model is described that implements context-dependent learning of complex sequences. The model utilises leaky integrate-and-fire neurons to extract timing inf...
Luc Berthouze, Adriaan G. Tijsseling