Zobrazeno 1 - 3
of 3
pro vyhledávání: '"David F. N. Oliveira"'
Autor:
David F. N. Oliveira, Lucio F. Vismari, Alexandre M. Nascimento, Jorge R. de Almeida, Paulo S. Cugnasca, Joao B. Camargo, Leandro Almeida, Rafael Gripp, Marcelo Neves
Publikováno v:
IEEE Access, Vol 10, Pp 1401-1409 (2022)
Despite the superior performance in modeling complex patterns to address challenging problems, the black-box nature of Deep Learning (DL) methods impose limitations to their application in real-world critical domains. The lack of a smooth manner for
Externí odkaz:
https://doaj.org/article/4aeec45dd4e04b509b89dd9a4e50482a
Autor:
David F. N. Oliveira, Lucio F. Vismari, Alexandre M. Nascimento, Jorge R. de Almeida, Paulo S. Cugnasca, Joao B. Camargo, Leandro Almeida, Rafael Gripp, Marcelo Neves
Publikováno v:
IEEE Access, Vol 10, Pp 1401-1409 (2022)
Despite the superior performance in modeling complex patterns to address challenging problems, the black-box nature of Deep Learning (DL) methods impose limitations to their application in real-world critical domains. The lack of a smooth manner for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ab1b3915bedfa042137bc09b108ed3c8
Autor:
Debora R. Doimo, Leandro P. F. de Almeida, Marcelo M. Neves, Rafael Gripp, Eduardo Marreto, David F. N. Oliveira, Lucio F. Vismari, João Batista Camargo, Jorge Rady de Almeida, Paulo Sérgio Cugnasca
Publikováno v:
ICMLA
Tuning a fault detector to balance false positive and false negative rates is fundamental to optimize maintenance operations. Unbalanced detectors can either lead to a high demand rate on the maintenance team (biased to false positives) or let failur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48a257699a9c6af49f845bf550b36eb4
https://doi.org/10.1109/icmla.2019.00172
https://doi.org/10.1109/icmla.2019.00172