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- W2147362258 abstract "This paper concerns estimation of the thickness of year rings by tomographic inspection of wood. Motivated by applications in the woodworking industry, we consider a setting where few tomographic data are available and classical reconstruction methods are not practicable. We introduce a stochastic model of the density of the wood in a log section. Based on this model, we derive a maximum likelihood and a nonlinear least squares estimator of the average ring thickness. Numerical simulations are reported showing the goodness of the model and the effectiveness of the estimators" @default.
- W2147362258 created "2016-06-24" @default.
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- W2147362258 date "2006-01-01" @default.
- W2147362258 modified "2023-10-16" @default.
- W2147362258 title "Identification of wood rings from sparse tomographic data" @default.
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- W2147362258 doi "https://doi.org/10.1109/cdc.2006.376923" @default.
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