Detection of defective part of inside manhole using deep learning for automation of inspection.

DOI

Bibliographic Information

Other Title
  • マンホール内部点検自動化のための深層学習を用いた不良箇所検出手法の検討

Description

<p>Currently, we inspect annually about 30 thousand manholes within NTT East’s jurisdiction. We take pictures of inside manhole using 360-degree camera on-site. The repair judgement of manhole is carried out visually by many people at the centralized inspection center. Using Convolutional Neural Network, which has been successful in the field of image recognition, is expected to reduce work amount of the visual check with automation of the repair judgment for manhole inspection photograph. In this study, we automate detection of defective part of inside manhole using Mask-RCNN. And we verified the detection accuracy.</p>

Journal

Keywords

Details 詳細情報について

  • CRID
    1390566775143058560
  • NII Article ID
    130007857326
  • DOI
    10.11517/pjsai.jsai2020.0_4l2gs1302
  • ISSN
    27587347
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

Report a problem

Back to top