Neural network-based adaptive sampling of 3D object surface elastic properties

TitleNeural network-based adaptive sampling of 3D object surface elastic properties
Publication TypeConference Paper
Year of Publication2004
AuthorsCretu, A. - M., E. M. Petriu, and G. G. Patry
Conference NameInstrumentation and Measurement Technology Conference, 2004. IMTC 04. Proceedings of the 21st IEEE
Pagination285 - 290 Vol.1
Date Publishedmay.
Keywords3D object surface elastic properties, data reduction, dexterous manipulators, dimensionality reduction, elasticity, image sampling, Kohonen self-organizing map, neural gas network, neural network-based adaptive sampling, nonuniform elastic property measurement, probing points, self-organising feature maps, self-organizing neural network architectures, shape measurement, stereo image processing

The paper discusses two self-organizing neural network (NN) architectures, the neural gas network and the Kohonen self-organizing map (SOM) for the adaptive sampling and the reduction of the dimensionality of the set of probing points in the measurement of the nonuniform elastic properties of 3D objects.


a place of mind, The University of British Columbia

Electrical and Computer Engineering
2332 Main Mall
Vancouver, BC Canada V6T 1Z4
Tel +1.604.822.2872
Fax +1.604.822.5949

Emergency Procedures | Accessibility | Contact UBC | © Copyright 2021 The University of British Columbia