Deep learning enhanced terahertz imaging of silkworm eggs development

Summary: Terahertz (THz) technology lays the foundation for next-generation high-speed wireless communication, nondestructive testing, food safety inspecting, and medical applications. When THz technology is integrated by artificial intelligence (AI), it is confidently expected that THz technology c...

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Autores principales:	Hongting Xiong, Jiahua Cai, Weihao Zhang, Jingsheng Hu, Yuexi Deng, Jungang Miao, Zhiyong Tan, Hua Li, Juncheng Cao, Xiaojun Wu
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Wave imaging Applied physics Machine learning Science Q
Acceso en línea:	https://doaj.org/article/09119776fa214cadb69366e919392a20
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id	oai:doaj.org-article:09119776fa214cadb69366e919392a20
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spelling	oai:doaj.org-article:09119776fa214cadb69366e919392a202021-11-20T05:09:53ZDeep learning enhanced terahertz imaging of silkworm eggs development2589-004210.1016/j.isci.2021.103316https://doaj.org/article/09119776fa214cadb69366e919392a202021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2589004221012852https://doaj.org/toc/2589-0042Summary: Terahertz (THz) technology lays the foundation for next-generation high-speed wireless communication, nondestructive testing, food safety inspecting, and medical applications. When THz technology is integrated by artificial intelligence (AI), it is confidently expected that THz technology could be accelerated from the laboratory research stage to practical industrial applications. Employing THz video imaging, we can gain more insights into the internal morphology of silkworm egg. Deep learning algorithm combined with THz silkworm egg images, rapid recognition of the silkworm egg development stages is successfully demonstrated, with a recognition accuracy of ∼98.5%. Through the fusion of optical imaging and THz imaging, we further improve the AI recognition accuracy of silkworm egg development stages to ∼99.2%. The proposed THz imaging technology not only features the intrinsic THz imaging advantages, but also possesses AI merits of low time consuming and high recognition accuracy, which can be extended to other application scenarios.Hongting XiongJiahua CaiWeihao ZhangJingsheng HuYuexi DengJungang MiaoZhiyong TanHua LiJuncheng CaoXiaojun WuElsevierarticleWave imagingApplied physicsMachine learningScienceQENiScience, Vol 24, Iss 11, Pp 103316- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Wave imaging Applied physics Machine learning Science Q
spellingShingle	Wave imaging Applied physics Machine learning Science Q Hongting Xiong Jiahua Cai Weihao Zhang Jingsheng Hu Yuexi Deng Jungang Miao Zhiyong Tan Hua Li Juncheng Cao Xiaojun Wu Deep learning enhanced terahertz imaging of silkworm eggs development
description	Summary: Terahertz (THz) technology lays the foundation for next-generation high-speed wireless communication, nondestructive testing, food safety inspecting, and medical applications. When THz technology is integrated by artificial intelligence (AI), it is confidently expected that THz technology could be accelerated from the laboratory research stage to practical industrial applications. Employing THz video imaging, we can gain more insights into the internal morphology of silkworm egg. Deep learning algorithm combined with THz silkworm egg images, rapid recognition of the silkworm egg development stages is successfully demonstrated, with a recognition accuracy of ∼98.5%. Through the fusion of optical imaging and THz imaging, we further improve the AI recognition accuracy of silkworm egg development stages to ∼99.2%. The proposed THz imaging technology not only features the intrinsic THz imaging advantages, but also possesses AI merits of low time consuming and high recognition accuracy, which can be extended to other application scenarios.
format	article
author	Hongting Xiong Jiahua Cai Weihao Zhang Jingsheng Hu Yuexi Deng Jungang Miao Zhiyong Tan Hua Li Juncheng Cao Xiaojun Wu
author_facet	Hongting Xiong Jiahua Cai Weihao Zhang Jingsheng Hu Yuexi Deng Jungang Miao Zhiyong Tan Hua Li Juncheng Cao Xiaojun Wu
author_sort	Hongting Xiong
title	Deep learning enhanced terahertz imaging of silkworm eggs development
title_short	Deep learning enhanced terahertz imaging of silkworm eggs development
title_full	Deep learning enhanced terahertz imaging of silkworm eggs development
title_fullStr	Deep learning enhanced terahertz imaging of silkworm eggs development
title_full_unstemmed	Deep learning enhanced terahertz imaging of silkworm eggs development
title_sort	deep learning enhanced terahertz imaging of silkworm eggs development
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/09119776fa214cadb69366e919392a20
work_keys_str_mv	AT hongtingxiong deeplearningenhancedterahertzimagingofsilkwormeggsdevelopment AT jiahuacai deeplearningenhancedterahertzimagingofsilkwormeggsdevelopment AT weihaozhang deeplearningenhancedterahertzimagingofsilkwormeggsdevelopment AT jingshenghu deeplearningenhancedterahertzimagingofsilkwormeggsdevelopment AT yuexideng deeplearningenhancedterahertzimagingofsilkwormeggsdevelopment AT jungangmiao deeplearningenhancedterahertzimagingofsilkwormeggsdevelopment AT zhiyongtan deeplearningenhancedterahertzimagingofsilkwormeggsdevelopment AT huali deeplearningenhancedterahertzimagingofsilkwormeggsdevelopment AT junchengcao deeplearningenhancedterahertzimagingofsilkwormeggsdevelopment AT xiaojunwu deeplearningenhancedterahertzimagingofsilkwormeggsdevelopment
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Deep learning enhanced terahertz imaging of silkworm eggs development

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