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» Terrain mapping and classification using neural networks
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CORR
2007
Springer
94views Education» more  CORR 2007»
14 years 9 months ago
Statistical tools to assess the reliability of self-organizing maps
Results of neural network learning are always subject to some variability, due to the sensitivity to initial conditions, to convergence to local minima, and, sometimes more dramat...
Eric de Bodt, Marie Cottrell, Michel Verleysen
IJCNN
2007
IEEE
15 years 4 months ago
Using Artificial Neural Networks and Feature Saliency Techniques for Improved Iris Segmentation
—One of the basic challenges to robust iris recognition is iris segmentation. This paper proposes the use of a feature saliency algorithm and an artificial neural network to perf...
Randy P. Broussard, Lauren R. Kennell, David L. So...
BMCBI
2010
149views more  BMCBI 2010»
14 years 9 months ago
A multifactorial analysis of obesity as CVD risk factor: Use of neural network based methods in a nutrigenetics context
Background: Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex eti...
Ioannis K. Valavanis, Stavroula G. Mougiakakou, Ke...
ICANN
1997
Springer
15 years 1 months ago
A Feature Map Approach to Pose Estimation Based on Quaternions
This paper proposes a novel solution to the problem of pose estimation of three-dimensional objects using feature maps. Our approach relies on quaternions as the mathematical repre...
S. Winkler, Patrick Wunsch, Gerd Hirzinger
ICANN
2010
Springer
14 years 10 months ago
Visualising Clusters in Self-Organising Maps with Minimum Spanning Trees
Abstract. The Self-Organising Map (SOM) is a well-known neuralnetwork model that has successfully been used as a data analysis tool in many different domains. The SOM provides a to...
Rudolf Mayer, Andreas Rauber