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Deep neural networks based approach for welded joint detection of oil pipelines in radiographic images with Double Wall Double Image exposure

  • Published:2019-07 Issue: Volume:105 Page:46-55
  • ISSN:0963-8695
  • Container-title:NDT & E International
  • language:en
  • Short-container-title:NDT & E International

Author:

Suyama Fernando Moreira,Delgado Myriam Regattieri,Dutra da Silva Ricardo,Centeno Tania Mezzadri

Funder

Coordination for the Improvement of Higher Education Personnel

National Council for Scientific and Technological Development

Publisher

Elsevier BV

Subject

Mechanical Engineering,Condensed Matter Physics,General Materials Science

Reference31 articles.

1. Automatic identification of different types of welding defects in radiographic images;Wang;NDT E Int,2002

2. Introduction to nondestructive testing;ASNT,2017

3. Real-time automatic detection of weld defects in steel pipe;Sun;NDT E Int,2005

4. Detection of line weld defects based on multiple thresholds and support vector machine;Wang;NDT E Int,2008

5. Automatic weld bead recognition and defect detection in pipeline radiographs;Felisberto,2006

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