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Registros recuperados: 49 | |
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ESQUERDO, J. C. D. M.. |
As imagens de satélite são uma fonte importante de informações sobre a superfície terrestre, pois sua visão sinóptica, temporal e multiespectral auxilia no entendimento dos processos que ocorrem nos ecossistemas terrestres. Ao longo dos anos, as pesquisas envolvendo o sensoriamento remoto na agricultura têm explorado a alta frequência de revisita de alguns sensores orbitais, como o Advanced Very High Resolution Radiometer (AVHRR), o Moderate Resolution Imaging Spectroradiometer (Modis) e o Vegetation, que fornecem imagens multiespectrais diárias da superfície terrestre, a partir das quais podem ser derivados produtos como índices de vegetação, temperatura de superfície, albedo de superfície, entre outros. |
Tipo: Folhetos |
Palavras-chave: Imagem de satélite; Imagem AVHRR; Satélite NOAA; Processamento de imagem; Image processing. |
Ano: 2011 |
URL: http://www.infoteca.cnptia.embrapa.br/infoteca/handle/doc/919171 |
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Meira,Luiz Antonio; Pereira,Lilian Elgalise Techio; Santos,Manoel Eduardo Rozalino; Tech,Adriano Rogério Bruno. |
ABSTRACT Computer vision systems based on digital image processing have been proposed as alternative tools to traditional methods to estimate leaf area, replacing the most time-consuming steps and laboring manual measurements. However, many of the available applications are still based on manual determination of leaf dimensions or require excessive and laborious user interventions before providing results. USPLeaf was designed to process images containing single or multiple leaves, and automatically determine the leaf area without user intervention. The accuracy for leaf area measurements of the software was compared to the results obtained by the standard method, an electronic planimeter (LI-3100). The vegetal species, Mavuno grass (MAV, Urochloa hybrid)... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Image processing; Edge detection; Image segmentation; Information extraction. |
Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902020000400413 |
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Wacquet, Guillaume; Grosjean, Philippe; Colas, Florent; Hamad, Denis; Artigas, Luis Felipe. |
The coupled system FlowCAM/ZooPhytoImage has become a real operational tool in 2014. However, to be fully adapted to the observations of phytoplankton performed in the context of the REPHY observation network and in order to better respond to present and future requests concerning the evaluation of quality of coastal and marine waters within the European requirements, such as the WFD and MSFD, new functionalities must be integrated into existing tools. Therefore, different axis of development have been proposed by UMONS and Ifremer to adapt both the digitization device and the Zoo/PhytoImage software to the constraints defined by the REPHY. First, version 5 of Zoo/PhytoImage contains recent innovations such as the development of routines to automatically... |
Tipo: Text |
Palavras-chave: Plancton; Analyse automatisée; Analyse d'image; Classification supervisée; Apprentissage actif; Dénombrement de cellules; Plankton; Automated analysis; Image processing; Supervised classification; Active learning; Cells counting. |
Ano: 2015 |
URL: http://archimer.ifremer.fr/doc/00389/49986/50573.pdf |
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Registros recuperados: 49 | |
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