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ORCIDEmanuel da S. D. Estrada
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2020 – today
- 2023
[c7]Mario Ricardo Nascimento Marques Junior, Eder Mateus Nunes Gonçalves
, Silvia Silva da Costa Botelho, Emanuel da Silva Diaz Estrada:
Data Digitalization and Conformity Verification in Oil and Gas Industry Databooks Using Semantic Model Based on Ontology. ICINCO (1) 2023: 180-187- 2021
- [c6]Mario Ricardo Nascimento Marques Junior, Eder Mateus Nunes Gonçalves, Silvia Silva da Costa Botelho, Emanuel da S. D. Estrada, Danúbia Bueno Espíndola, Eduardo Nunes Borges, Werner Luft Botelho, Bruno Machado Lobell, Lucas Silva Marca:
System Proposal for Integrating Quality Control Data of Components of the Brazilian Oil and Gas Industry. ICINCO 2021: 211-215 - [c5]Nelson de Farias Traversi, Douglas Alves Goulart, Julio Cezar O. Mendonça, Silvia S. C. Botelho, Luciane B. Soares, Emanuel da S. D. Estrada, Paulo L. J. Drews-Jr, Vinícius Menezes de Oliveira:
VBM granulometry for real applications in the fertilizer industry. LARS/SBR/WRE 2021: 276-281 - 2020
- [c4]Douglas Alves Goulart, Nelson de Farias Traversi, Julio Cezar O. Mendonça, Ricardo Nagel Rodrigues, Emanuel da S. D. Estrada, Paulo Lilles Drews Jr., Vinicius Menezes de Oliveira, Silvia S. C. Botelho:
Grain Surface Simulator to Averiguate the Overlapping and Noise Problems on Computer Vision Granullometry of Fertilizers. INDIN 2020: 374-379
2010 – 2019
- 2019
- [c3]Júlio Mendonça, Marta Duarte, Victor Coch, Emanuel da S. D. Estrada, Ricardo Rodrigues, Silvia Botelho:
Granulometric Analysis of Fertilizers by Digital Image Processing. INDIN 2019: 73-78 - [c2]Gabriel Lavoura dos Santos, Vanessa Telles da Silva, Fabiano Sandrini Moraes, Emanuel da Silva Diaz Estrada, Vagner Santos Da Rosa:
Development of an Embedded System for Use in Real-Time Intelligent Traps to Detecting Fruit Fly (Diptera: Tephritidae). LARS/SBR/WRE 2019: 210-215 - [c1]Bryan Stefan Galani Pernambuco, Cristiano Rafael Steffens, Jefferson R. Pereira, Adriano Velasque Werhli, Rodrigo Zelir Azzolin, Emanuel da Silva Diaz Estrada:
Online Sound Based Arc-Welding Defect Detection Using Artificial Neural Networks. LARS/SBR/WRE 2019: 263-268
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