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TXT e-solutions (Italy)

Italy

1 paper here1 citations across 1
fields
  • cs.NI1
ROR 01h89k731OpenAlex

affiliations via OpenAlex

most citedAn End-To-End Analysis of Deep Learning-Based Remaining Useful Life Algorithms for Satefy-Critical 5G-Enabled IIoT Networks

1 citations

researchers with a paper here
  • Enrico Buracchini1
  • Giampaolo Cuozzo1
  • Lorenzo Mario Amorosa1
  • Nicolò Longhi1
  • Roberto Verdone1
  • Valerio Lieti1
  • Weronika Maria Bachan1
collaborating institutions
  • CNH Industrial (Italy)IT1 paper
  • Nokia (Italy)IT1 paper
  • Telecom Italia (Italy)IT1 paper
  • University of BolognaIT1 paper

1 paper

cs.NI2023★ 1 cited

An End-To-End Analysis of Deep Learning-Based Remaining Useful Life Algorithms for Satefy-Critical 5G-Enabled IIoT Networks

Lorenzo Mario Amorosa, Nicolò Longhi, Giampaolo Cuozzo +4

Remaining Useful Life (RUL) prediction is a critical task that aims to estimate the amount of time until a system fails, where the latter is formed by three main components, that i…

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