Machine-learning reprogrammable metasurface imager

Conventional imagers require time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing. Here, the authors demonstrate a real-time digital-metasurface imager that can be trained in-situ to show high accuracy image coding and recognition for various image sets.

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Detalles Bibliográficos
Autores principales:	Lianlin Li, Hengxin Ruan, Che Liu, Ying Li, Ya Shuang, Andrea Alù, Cheng-Wei Qiu, Tie Jun Cui
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/c5917dd7c6f245c1b84dfdc385f4e437
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id	oai:doaj.org-article:c5917dd7c6f245c1b84dfdc385f4e437
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spelling	oai:doaj.org-article:c5917dd7c6f245c1b84dfdc385f4e4372021-12-02T17:31:37ZMachine-learning reprogrammable metasurface imager10.1038/s41467-019-09103-22041-1723https://doaj.org/article/c5917dd7c6f245c1b84dfdc385f4e4372019-03-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-09103-2https://doaj.org/toc/2041-1723Conventional imagers require time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing. Here, the authors demonstrate a real-time digital-metasurface imager that can be trained in-situ to show high accuracy image coding and recognition for various image sets.Lianlin LiHengxin RuanChe LiuYing LiYa ShuangAndrea AlùCheng-Wei QiuTie Jun CuiNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-8 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Lianlin Li Hengxin Ruan Che Liu Ying Li Ya Shuang Andrea Alù Cheng-Wei Qiu Tie Jun Cui Machine-learning reprogrammable metasurface imager
description	Conventional imagers require time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing. Here, the authors demonstrate a real-time digital-metasurface imager that can be trained in-situ to show high accuracy image coding and recognition for various image sets.
format	article
author	Lianlin Li Hengxin Ruan Che Liu Ying Li Ya Shuang Andrea Alù Cheng-Wei Qiu Tie Jun Cui
author_facet	Lianlin Li Hengxin Ruan Che Liu Ying Li Ya Shuang Andrea Alù Cheng-Wei Qiu Tie Jun Cui
author_sort	Lianlin Li
title	Machine-learning reprogrammable metasurface imager
title_short	Machine-learning reprogrammable metasurface imager
title_full	Machine-learning reprogrammable metasurface imager
title_fullStr	Machine-learning reprogrammable metasurface imager
title_full_unstemmed	Machine-learning reprogrammable metasurface imager
title_sort	machine-learning reprogrammable metasurface imager
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/c5917dd7c6f245c1b84dfdc385f4e437
work_keys_str_mv	AT lianlinli machinelearningreprogrammablemetasurfaceimager AT hengxinruan machinelearningreprogrammablemetasurfaceimager AT cheliu machinelearningreprogrammablemetasurfaceimager AT yingli machinelearningreprogrammablemetasurfaceimager AT yashuang machinelearningreprogrammablemetasurfaceimager AT andreaalu machinelearningreprogrammablemetasurfaceimager AT chengweiqiu machinelearningreprogrammablemetasurfaceimager AT tiejuncui machinelearningreprogrammablemetasurfaceimager
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Machine-learning reprogrammable metasurface imager

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