Preliminary study of artificial intelligence-based fuel-rod pattern analysis of low-quality tomographic image of fuel assembly-Reference-Cited by-同舟云学术

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Preliminary study of artificial intelligence-based fuel-rod pattern analysis of low-quality tomographic image of fuel assembly

Published:2022-10 Issue:10 Volume:54 Page:3943-3948
ISSN:1738-5733
Container-title:Nuclear Engineering and Technology
language:en
Short-container-title:Nuclear Engineering and Technology

Author:

Seong Saerom,Choi Sehwan,Ahn Jae Joon,Choi Hyung-joo,Chung Yong Hyun,You Sei Hwan,Yeom Yeon Soo^ORCID,Choi Hyun Joon^ORCID,Min Chul Hee^ORCID

Publisher

Elsevier BV

Subject

Nuclear Energy and Engineering

Reference18 articles.

1. Additional Detection Techniques under Development, Spent Nuclear Fuel Safeguards;Sweeney,2017

2. Safeguards in the Design of Facilities for Long Term Spent Fuel Management;International,2018

3. IAEA safeguards equipment;Zendel;Int. J. Nucl. Sci. Technol.,2008

4. Prototype Tomographic Partial Defect Tester;Honkamaa,2006

5. Prototype tomographic partial defect tester: project status update;Honkamaa,2007

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Corrigendum to “Preliminary study of artificial intelligence-based fuel-rod pattern analysis of low-quality tomographic image of fuel assembly” [Nucl. Eng. Technol. 54 (10) (2022) 3943–3948];Nuclear Engineering and Technology;2024-09

2. Image reconstruction method of gamma emission tomography based on prior-aware information and machine learning for partial-defect detection of PWR-type spent nuclear fuel;Nuclear Engineering and Technology;2024-06

3. Heat-vision based drone surveillance augmented by deep learning for critical industrial monitoring;Scientific Reports;2023-12-15

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