Abstract
Reconstruction and manufacturing of existing freeform surfaces are of paramount importance for reverse engineering. The paper presents support vector regression (SVR) to reconstruction of computer models for existing freeform surfaces. Through examples, the effective is compared among different methods, and the influence of kernels to the precision is discussed. The results show that SVR is better than the algorithms given in (mising data), when it is used to reconstruct freeform surface.
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© 2005 International Federation for Information Processing
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Jing, L., Zhen, L. (2005). Reconstruction of Freeform Surface by Support Vector Regression. In: Li, D., Wang, B. (eds) Artificial Intelligence Applications and Innovations. AIAI 2005. IFIP — The International Federation for Information Processing, vol 187. Springer, Boston, MA. https://doi.org/10.1007/0-387-29295-0_42
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DOI: https://doi.org/10.1007/0-387-29295-0_42
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-28318-0
Online ISBN: 978-0-387-29295-3
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