Implementation of surface crack detection method for nuclear fuel pellets by weakly supervised learning

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-07-07 DOI:10.1080/00223131.2024.2371961

Fengyu Li, Bin Zhang, Bin Zhang, Fanghui Zhang, Qingtao Zhao, Shiyang Lou, Zhiyong Wang, Kaixin Huang

引用次数: 0

Abstract

Surface cracks are one of the primary defects in nuclear fuel pellets, posing a significant hazard to nuclear safety production. Deep learning-based methods recently developed for crack detection a...

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通过弱监督学习实现核燃料芯块表面裂纹检测方法

表面裂纹是核燃料芯块的主要缺陷之一，对核安全生产构成重大危害。最近开发的基于深度学习的裂纹检测和分析方法可用于核燃料芯块的表面裂纹检测。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.