Zobrazeno 1 - 5 of 5 pro vyhledávání: '"Leo Araújo"'
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Akademický článek
Spatio-Temporal Deep Learning-Based Methods for Defect Detection: An Industrial Application Study Case
Autor: Lucas A. da Silva, Eulanda M. dos Santos, Leo Araújo, Natalia S. Freire, Max Vasconcelos, Rafael Giusti, David Ferreira, Anderson S. Jesus, Agemilson Pimentel, Caio F. S. Cruz, Ruan J. S. Belem, André S. Costa, Osmar A. da Silva
Publikováno v: Applied Sciences, Vol 11, Iss 22, p 10861 (2021)
Data-driven methods—particularly machine learning techniques—are expected to play a key role in the headway of Industry 4.0. One increasingly popular application in this context is when anomaly detection is employed to test manufactured goods in
Externí odkaz: https://doaj.org/article/767bfa1dee5a46788481ad3eea69f2e1
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2
Quadro de Anosmia pós-infecção por Covid-19
Autor: João Wilton Lucena Bessa, André Sousa Bizerril, Isabella Santos Tomaz, Kadmiel Lima do Amaral, Leo Araújo Oliveira, Pedro Augusto Dodt Bezerra, Pedro Henrique Pinheiro Costa, Rafael Carneiro Magalhães, Rodrigo Matos Freitas, Raquel de Oliveira Monteiro Tavares
Publikováno v: Revista Eletrônica Acervo Médico. 14:e10672
Objetivo: Discutir a anosmia após um quadro infeccioso por Covid-19 e suas principais características e implicações na saúde humana. Revisão Bibliográfica: Como principais fatores de risco levantados pela presente revisão, tem-se a idade e o
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ccd6d0885a4d70c1ac5f6f94af01f677
https://doi.org/10.25248/reamed.e10672.2022
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5
Spatio-Temporal Deep Learning-Based Methods for Defect Detection: An Industrial Application Study Case
Autor: Andre S. Costa, Ruan J.S. Belem, Eulanda Miranda dos Santos, Max Vasconcelos, Osmar A. da Silva, Leo Araújo, Caio F.S. Cruz, David Alan de Oliveira Ferreira, Natalia de Sousa Freire, Lucas A. da Silva, Anderson S. Jesus, Rafael Giusti, Agemilson Pimentel
Publikováno v: Applied Sciences, Vol 11, Iss 10861, p 10861 (2021)
Applied Sciences
Volume 11
Issue 22
Data-driven methods—particularly machine learning techniques—are expected to play a key role in the headway of Industry 4.0. One increasingly popular application in this context is when anomaly detection is employed to test manufactured goods in
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cae20e3a2a9123a30f279d31af56cac7
https://doi.org/10.3390/app112210861
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