A neural network algorithm to simplify 2D meshes

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/25298
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Title: A neural network algorithm to simplify 2D meshes
Authors: Martínez Pérez, Francisco M. | Oliver, Jose-Luis | Tortosa, Leandro | Vicent, Jose F.
Research Group/s: Criptología y Seguridad Computacional | Arquitectura - Composición Arquitectónica (CA01) | Urbanística y Ordenación del Territorio en el Espacio Litoral
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial | Universidad de Alicante. Departamento de Expresión Gráfica y Cartografía
Keywords: Neural networks | Self-organizing maps | Mesh simplification | GNG3D algorithm | Triangulations
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial | Composición Arquitectónica
Issue Date: 2011
Publisher: WSEAS
Citation: MARTÍNEZ, Francisco-M., et al. "A neural network algorithm to simplify 2D meshes". En: Recent Advances in Computers, Communications, Applied Social Science and Mathematics : Barcelona, Spain, September 15-17, 2011. [S.l.] : WSEAS, 2011. ISBN 978-1-61804-030-5, pp. 110-115
Abstract: In this paper we propose a neural network model to simplify and 2D meshes. This model is based on the Growing Neural Gas model and is able to simplify any mesh with different topologies and sizes. A triangulation process is included with the objective to reconstruct the mesh. This model is applied to some problems related to urban networks.
Sponsor: Partially supported by UA grant number GRE10-34.
URI: http://hdl.handle.net/10045/25298
ISBN: 978-1-61804-030-5
Language: eng
Type: info:eu-repo/semantics/conferenceObject
Rights: Copyright © 2011 WSEAS
Peer Review: si
Appears in Collections:INV - CSC - Comunicaciones a Congresos, Conferencias, etc.
INV - CA01 - Comunicaciones a Congresos, Conferencias, etc.
INV - UOTEL - Comunicaciones a Congresos, Conferencias, etc.
INV - ANVIDA - Comunicaciones a Congresos, Conferencias, etc.

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