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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
15/10/2007 |
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Data da última atualização: |
21/07/2025 |
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Autoria: |
LEBOW, P. K.; BRUNNER, C. C.; MARISTANY, A. G.; BUTLER, D. A. |
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Título: |
Classification of wood surface features by spectral reflectance. |
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Ano de publicação: |
1996 |
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Fonte/Imprenta: |
Separata de: Wood and Fiber Science, v. 28, n. 1, p. 74-90, 1996. |
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Idioma: |
Inglês |
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Conteúdo: |
A database of spectral-reflectance curves of Douglas-fir veneer surface features is presented and analyzed via principal-component analysis. The paper describes how such analysis can be used to model and classify the spectral-reflectance curves by feature type. For modeling (curve-reconstruction) purposes, three principal components were sufficient by most criteria. For classification purposes, seven principal components achieved classification accuracies (with quadratic discriminant analysis) on the order of 99%, comparable to the accuracies achieved with the raw spectral data. The best seven principal components were not those associated with the largest variation in the data. This paper suggests how comparable classification accuracies might be achieved in a system operating at production speeds in a mill. |
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Palavras-Chave: |
Classificação; Reflectância difusa; Spectral reflectance. |
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Thesagro: |
Madeira. |
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Thesaurus Nal: |
classification; wood. |
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Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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Marc: |
LEADER 01474naa a2200229 a 4500
001 1312976
005 2025-07-21
008 1996 bl uuuu u00u1 u #d
100 1 $aLEBOW, P. K.
245 $aClassification of wood surface features by spectral reflectance.$h[electronic resource]
260 $c1996
520 $aA database of spectral-reflectance curves of Douglas-fir veneer surface features is presented and analyzed via principal-component analysis. The paper describes how such analysis can be used to model and classify the spectral-reflectance curves by feature type. For modeling (curve-reconstruction) purposes, three principal components were sufficient by most criteria. For classification purposes, seven principal components achieved classification accuracies (with quadratic discriminant analysis) on the order of 99%, comparable to the accuracies achieved with the raw spectral data. The best seven principal components were not those associated with the largest variation in the data. This paper suggests how comparable classification accuracies might be achieved in a system operating at production speeds in a mill.
650 $aclassification
650 $awood
650 $aMadeira
653 $aClassificação
653 $aReflectância difusa
653 $aSpectral reflectance
700 1 $aBRUNNER, C. C.
700 1 $aMARISTANY, A. G.
700 1 $aBUTLER, D. A.
773 $tSeparata de: Wood and Fiber Science$gv. 28, n. 1, p. 74-90, 1996.
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| 1. |  | HILL, R.; NATES-PARRA, G.; QUEZADA-EUÁN, J. J. G.; BUCHORI, D.; LEBUHN, G.; MAUES, M. M.; PERT, P. L.; KWAPONG, P. K.; SAEED, S.; BRESLOW, S. J.; CUNHA, M. C. da; DICKS, L. V.; GALETTO, L.; GIKUNGU, M.; HOWLETT, B. G.; IMPERATRIZ-FONSECA, V. L.; LYVER, P. O'B.; MARTÍN-LÓPEZ, B.; OTEROS-ROZAS, E.; POTTS, S. G.; ROUÉ, M. Biocultural approaches to pollinator conservation. Nature Sustainability, v.2, p. 214-222, mar. 2019.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 4 |
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