Nature Communications (Mar 2019)

Machine-learning reprogrammable metasurface imager

  • Lianlin Li,
  • Hengxin Ruan,
  • Che Liu,
  • Ying Li,
  • Ya Shuang,
  • Andrea Alù,
  • Cheng-Wei Qiu,
  • Tie Jun Cui

DOI
https://doi.org/10.1038/s41467-019-09103-2
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 8

Abstract

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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.