Applying SDR with CNN to Identify Weld Defect: A New Processing Method-Reference-Cited by-同舟云学术

Applying SDR with CNN to Identify Weld Defect: A New Processing Method

Published:2023-05 Issue:2 Volume:14 Page:
ISSN:1949-1190
Container-title:Journal of Pipeline Systems Engineering and Practice
language:en
Short-container-title:J. Pipeline Syst. Eng. Pract.

Author:

Wang Zheng¹^ORCID,Gao Weixin²,Song Jiuxu³

Affiliation:

1. Lecturer, Dept. of Electrical Engineering, Xi’an Shi You Univ., Xi’an dianzi er lu, Xi’an, Shaanxi 710065, China (corresponding author). ORCID: .

2. Professor, Dept. of Electrical Engineering, Xi’an Shi You Univ., Xi’an dianzi er lu, Xi’an, Shaanxi 710065, China.

3. Associate Professor, Dept. of Electrical Engineering, Xi’an Shi You Univ., Xi’an dianzi er lu, Xi’an, Shaanxi 710065, China.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Mechanical Engineering,Civil and Structural Engineering

Link

https://ascelibrary.org/doi/pdf/10.1061/JPSEA2.PSENG-1380

Reference30 articles.

1. Efficient detection of glaucoma using double tier deep convolutional neural network;Babu C. M.;Pers. Ubiquitous Comput.,2022

2. Recurrent neural network-based multiaxial plasticity model with regularization for physics-informed constraints

3. Otsu’s image segmentation algorithm with memory-based fruit fly optimization algorithm;Chai R. S.;Complexity,2021

4. Automatic recognition of weld defects in x-ray inspection—Reconnaissance automatique des défauts d’une soudure inspectée aux Rayons X;Daum W.;Br. J. Nondestr. Test.,1987

5. Automatic recognition of welding defects in real-time radiography

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