Inferring shape evolution.
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Date
2003
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Abstract
Dynamic shapes represent an important issue in several scientific and technological contexts. The current article presents a model-based mathematic-computational approach for inferring the processes of neural evolution, including analytical mappings, convolution models and normal wavefront propagation, illustrated with respect to stationary and non-stationary evolutions along time and space.
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Keywords
Correspondence, Normal evolution, Shape dynamics
Citation
BIANCHI, A. G. C. et al. Inferring shape evolution. Pattern Recognition Letters, v. 24, n. 7, p. 1005-1014, abr. 2003. Disponível em: <https://www.sciencedirect.com/science/article/pii/S0021997506000594>. Acesso em: 10 jul. 2012.