| |
|
|
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Hortaliças. |
|
Data corrente: |
18/05/1999 |
|
Data da última atualização: |
18/05/1999 |
|
Autoria: |
CASTELO BRANCO, M.; GUIMARAES, A. L.; REIFSCHNEIDER, F. J. B.; BOITEUX, L. S. |
|
Afiliação: |
EMBRAPA-CNPH, Brasilia, DF. |
|
Título: |
Falta de eficiencia de metodos alternativos para o controle de oidio em abobrinha. |
|
Ano de publicação: |
1989 |
|
Fonte/Imprenta: |
Horticultura Brasileira, Brasilia, v.7, n.1, p.30-31, maio 1989. |
|
Idioma: |
Português |
|
Palavras-Chave: |
Abobrinha; Brasil; Brasilia; Control; Controle; Cultivar Caserta; Distrito Federal. |
|
Thesagro: |
Cerrado; Cucúrbita Pepo; Oídio. |
|
Thesaurus Nal: |
Brazil; Oidium; Sphaerotheca fuliginea; zucchini. |
|
Categoria do assunto: |
-- |
|
Marc: |
LEADER 00840naa a2200313 a 4500
001 1764120
005 1999-05-18
008 1989 bl uuuu u00u1 u #d
100 1 $aCASTELO BRANCO, M.
245 $aFalta de eficiencia de metodos alternativos para o controle de oidio em abobrinha.
260 $c1989
650 $aBrazil
650 $aOidium
650 $aSphaerotheca fuliginea
650 $azucchini
650 $aCerrado
650 $aCucúrbita Pepo
650 $aOídio
653 $aAbobrinha
653 $aBrasil
653 $aBrasilia
653 $aControl
653 $aControle
653 $aCultivar Caserta
653 $aDistrito Federal
700 1 $aGUIMARAES, A. L.
700 1 $aREIFSCHNEIDER, F. J. B.
700 1 $aBOITEUX, L. S.
773 $tHorticultura Brasileira, Brasilia$gv.7, n.1, p.30-31, maio 1989.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Hortaliças (CNPH) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
Registro Completo
|
Biblioteca(s): |
Embrapa Agroindústria de Alimentos. |
|
Data corrente: |
16/10/2023 |
|
Data da última atualização: |
16/10/2023 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Circulação/Nível: |
A - 3 |
|
Autoria: |
HIDALGO CHÁVEZ, D. W.; SILVA, F. L. C. DA; PINTO, R. V.; CARVALHO, C. W. P. de; FREITAS-SILVA, O. |
|
Afiliação: |
DAVY WILLIAM HIDALGO CHÁVEZ, UFRRJ; FELIPE LEITE COELHO DA SILVA, UFRRJ; RENAN VICENTE PINTO, UFRRJ; CARLOS WANDERLEI PILER DE CARVALHO, CTAA; OTNIEL FREITAS SILVA, CTAA. |
|
Título: |
Streamlined approaches for image classification using principal component analysis and hierarchical clustering of extrudates from coffee and sorghum blends. |
|
Ano de publicação: |
2023 |
|
Fonte/Imprenta: |
CyTA: Journal of Food, v. 21, n. 1, p. 606-613, 2023. |
|
DOI: |
https://doi.org/10.1080/19476337.2023.2263513 |
|
Idioma: |
Inglês |
|
Conteúdo: |
This article describes simple methods to group images including principal component analysis (PCA) and hierarchical clustering of principal components (HCPC). Images of expanded and low expanded extrudates were processed using two optimization alternatives: a) image size reduction (from 2126 to 25 pixels); and b) grayscale conversion before size reduction. After applying PCA and HCPC, all tests yielded consistently similar results with the same PCA distribution and identical HCPC groups. Furthermore, expanded and low expanded extrudates formed groups with their respective peers. The RAM allocated to images and the time required to process them was reduced from 1727 Mb to less than 5 Mb and from ~ 2000s to just 0.1s, respectively. These results demonstrate the e feasibility of using these two simple multivariate statistical techniques for image classification. |
|
Palavras-Chave: |
Image classification. |
|
Thesaurus NAL: |
Image analysis; Principal component analysis. |
|
Categoria do assunto: |
-- |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1157235/1/Streamlined-approaches-for-image-classification-using-principal-component-analysis-and-hierarchical-clustering-of-extrudates-from-coffee-and-sorghum-b.pdf
|
|
Marc: |
LEADER 01652naa a2200217 a 4500
001 2157235
005 2023-10-16
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1080/19476337.2023.2263513$2DOI
100 1 $aHIDALGO CHÁVEZ, D. W.
245 $aStreamlined approaches for image classification using principal component analysis and hierarchical clustering of extrudates from coffee and sorghum blends.$h[electronic resource]
260 $c2023
520 $aThis article describes simple methods to group images including principal component analysis (PCA) and hierarchical clustering of principal components (HCPC). Images of expanded and low expanded extrudates were processed using two optimization alternatives: a) image size reduction (from 2126 to 25 pixels); and b) grayscale conversion before size reduction. After applying PCA and HCPC, all tests yielded consistently similar results with the same PCA distribution and identical HCPC groups. Furthermore, expanded and low expanded extrudates formed groups with their respective peers. The RAM allocated to images and the time required to process them was reduced from 1727 Mb to less than 5 Mb and from ~ 2000s to just 0.1s, respectively. These results demonstrate the e feasibility of using these two simple multivariate statistical techniques for image classification.
650 $aImage analysis
650 $aPrincipal component analysis
653 $aImage classification
700 1 $aSILVA, F. L. C. DA
700 1 $aPINTO, R. V.
700 1 $aCARVALHO, C. W. P. de
700 1 $aFREITAS-SILVA, O.
773 $tCyTA: Journal of Food$gv. 21, n. 1, p. 606-613, 2023.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Agroindústria de Alimentos (CTAA) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Expressão de busca inválida. Verifique!!! |
|
|
