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A fine-tuning deep learning framework to palliate data distribution shift effects in rotary machine fault detection

Author(s): ORCID (Department of Engineering, University of Campania “L. Vanvitelli,” Aversa, Italy)
ORCID (Department of Engineering, University of Campania “L. Vanvitelli,” Aversa, Italy)
ORCID (College of Engineering, Birmingham City University, Birmingham, UK)
ORCID (Department of Engineering, University of Campania “L. Vanvitelli,” Aversa, Italy)
(Department of Engineering, University of Campania “L. Vanvitelli,” Aversa, Italy)
Medium: journal article
Language(s): English
Published in: Structural Health Monitoring
DOI: 10.1177/14759217241295951
Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1177/14759217241295951.
  • About this
    data sheet
  • Reference-ID
    10812137
  • Published on:
    17/01/2025
  • Last updated on:
    17/01/2025
 
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