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| Tedesco,Leonel P. C.; Freitas,Adriano da C. de; Molz,Rolf F.; Schreiber,Jacques N. C.. |
| ABSTRACT This article proposes an automatic method for classification of cured tobacco leaves. Typically this process is performed manually, allowing the occurrence of human errors. In addition, the existence of an automated comparative procedure, helping to perform the classification, can make this process faster and more transparent. In order to implement the method, non-invasive to the agricultural product, 250 samples of Virginia tobacco digital images in the RGB and HSV color models were analyzed. The validation of the method was carried out using partial least squares (PLS) and artificial neural network (ANN), presenting a qualitative and quantitative analysis of both tools. It has been verified that the PLS can be applied to this method, as it has a... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Image processing; Partial least square; Artificial neural network. |
| Ano: 2019 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662019001000782 |
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| Costa, Corrado; Sperandio, Giulio; Verani, Stefano. |
| Agricultural biomass supply chain consisting of multiple harvesting, storage, pre-processing, and transport operations. This network operates in space and time coordinates and produces empirical data used for many purposes, including wood-flow planning, harvesting cost calculation and work rate setting. The aim of this study was to explore and propose the use of a multivariate approach, namely, the Partial Least Squares (PLS) multivariate regression approach and compare its performance with the commonly used Ordinary Linear Regression (OLS). In particular, the study aimed at comparing the main statistical significance of indicators attributed to models calculated with OLS and PLS regressions from the same original datasets, for the purpose of... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Harvesting; Biomass; Logistics; Machine costs; Multivariate statistics; Ordinary linear regression; Partial least square. |
| Ano: 2014 |
URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/2910 |
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