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Registro Completo |
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Biblioteca(s): |
Embrapa Instrumentação. |
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Data corrente: |
09/06/2022 |
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Data da última atualização: |
23/01/2024 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
ALVES, G. M.; CRUVINEL, P. E. |
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Afiliação: |
PAULO ESTEVAO CRUVINEL, CNPDIA. |
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Título: |
Tomographic image reconstruction method using mapreduce in big data environment. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
In: IEEE International Conference on Semantic Computing (ICSC), 16th, Laguna Hills, CA, USA, 2022. |
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Páginas: |
293 - 298 |
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ISBN: |
978-1-6654-3418-8 |
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ISSN: |
2325-6516 |
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Idioma: |
Inglês |
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Conteúdo: |
In this study, we propose a new tomographic reconstruction method for high-resolution samples based on the MapReduce model. We executed the method in a big data environment with a cluster installed on the Amazon Web Services (AWS) platform. The big data environment framework considered four sets of matrices from a single heterogeneous plexiglass phantom sample, totaling 7,840 matrices (35.63 GB) processed by 12 different frameworks and producing 427.56 GB of processed tomographic data. The proposed method enabled the analysis of large numbers of agricultural samples using X-ray tomography to support management based on precision agriculture paradigms,the decision-making processes of which require an increasing number of analyses. |
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Palavras-Chave: |
Big data; MapReduce; Tomographic image reconstruction. |
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Categoria do assunto: |
-- |
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Marc: |
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Registro original: |
Embrapa Instrumentação (CNPDIA) |
