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Approaches for improvement of the X-ray image defect detection of automobile casting aluminum parts based on deep learning

  • Published:2019-10 Issue: Volume:107 Page:102144
  • ISSN:0963-8695
  • Container-title:NDT & E International
  • language:en
  • Short-container-title:NDT & E International

Author:

Du Wangzhe,Shen Hongyao,Fu Jianzhong,Zhang Ge,He Quan

Funder

Science Fund for Creative Research Groups

National Natural Science Foundation of China

Key Research and Development Plan of Zhejiang Province

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Mechanical Engineering,Condensed Matter Physics,General Materials Science

Reference42 articles.

1. Defects, causes and their remedies in casting process: a review;Rajkolhe;Int. J. Res. Advent. Technol.,2014

2. Automatic defect detection on hot-rolled flat steel products;Ghorai;IEEE Trans Instrum Meas,2013

3. Detection and segmentation of manufacturing defects with convolutional neural networks and transfer learning;Ferguson;Smart Sustain Manuf Syst,2018

4. Advanced 3D failure characterization in multi-layered PCBs;Grunwald;NDT E Int,2016

5. Ultrasonic analysis and lock-in thermography for debonding evaluation of composite adhesive joints;Palumbo;NDT E Int,2016

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