Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/91543
Title: A new machine learning paradigm for terrain reconstruction
Authors: Huang, Guang-Bin
Yeu, Thomas Chee Wee
Lim, Meng-Hiot
Agarwal, Amit
Ong, Yew Soon
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
Issue Date: 2006
Source: Yeu, C. W., Lim, M. H., Huang, G. B., Agarwal, A., & Ong, Y. S. (2006). A new machine learning paradigm for terrain reconstruction. Geoscience and Remote Sensing Letters. 3(3), 382-386.
Series/Report no.: Geoscience and remote sensing letters
Abstract: Terrain models that permit multiresolution access are essential for model predictive control of unmanned aerial vehicles in low-level flights. The authors present the extreme learning machine (ELM), a recently proposed learning paradigm, as a mechanism for learning the stored digital elevation information to allow multiresolution access. We give results of simulations designed to compare the performance of our approach with two other approaches for multiresolution access, namely: 1) linear interpolation on Delaunay triangles of the sampled terrain data points and 2) terrain learning using support vector machines (SVMs). The results show that to achieve the same mean square error during access, the memory needed in our approach is significantly lower. Additionally, the offline training time for the ELM network is much less than that for the SVM.
URI: https://hdl.handle.net/10356/91543
http://hdl.handle.net/10220/6308
ISSN: 1545-598X
DOI: 10.1109/LGRS.2006.873687
Rights: © 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. http://www.ieee.org/portal/site This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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