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Hybrid Functional-Neural Approach for Surface Reconstruction
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-01-16
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
This paper introduces a new hybrid functional-neural approach for surface reconstruction.
Our approach is based on the combination of two powerful artificial intelligence paradigms: on one hand, we apply the popular Kohonen neural network to address the data parameterization problem.
On the other hand, we introduce a new functional network, called NURBS functional network, whose topology is aimed at reproducing faithfully the functional structure of the NURBS surfaces.
These neural and functional networks are applied in an iterative fashion for further surface refinement.
The hybridization of these two networks provides us with a powerful computational approach to obtain a NURBS fitting surface to a set of irregularly sampled noisy data points within a prescribed error threshold.
The method has been applied to two illustrative examples.
The experimental results confirm the good performance of our approach.
American Psychological Association (APA)
Iglesias, Andrés& Gálvez, Akemi. 2014. Hybrid Functional-Neural Approach for Surface Reconstruction. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-465041
Modern Language Association (MLA)
Iglesias, Andrés& Gálvez, Akemi. Hybrid Functional-Neural Approach for Surface Reconstruction. Mathematical Problems in Engineering No. 2014 (2014), pp.1-13.
https://search.emarefa.net/detail/BIM-465041
American Medical Association (AMA)
Iglesias, Andrés& Gálvez, Akemi. Hybrid Functional-Neural Approach for Surface Reconstruction. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-13.
https://search.emarefa.net/detail/BIM-465041
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-465041