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文章基本信息

  • 标题:Distribution Line Equipment and Defect Identification Based on Deep Learning
  • 本地全文:下载
  • 作者:Gege Chen
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2021
  • 卷号:261
  • 页码:1-5
  • DOI:10.1051/e3sconf/202126101011
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:In this study, UAVs were used to collect data of distribution line resources, and defects in distribution line equipment and construction process were identified through deep learning. Different algorithms are used to identify the defects of distribution line equipment and construction process. The research will ultimately support regional synchronization and online development for intelligent automatic acceptance of the distribution wire UAV.
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