The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Machine-learning reprogrammable metasurface imager
Open accessAbstract
Conventional microwave imagers usually require either time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing, making them largely ineffective for complex in-situ sensing and monitoring. Here, we experimentally report a real-time digital-metasurface imager that can be trained in-situ to generate the radiation patterns required by machine-learning optimized measurement modes. This imager is electronically reprogrammed in real time to access the optimized solution for an entire data set, realizing storage and transfer of full-resolution raw data in dynamically varying scenes. High-accuracy image coding and recognition are demonstrated in situ for various image sets, including hand-written digits and through-wall body gestures, using a single physical hardware imager, reprogrammed in real time. Our electronically controlled metasurface imager opens new venues for intelligent surveillance, fast data acquisition and processing, imaging at various frequencies, and beyond.
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Self-citationProbabilistic Principal Component Analysis
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Electromagnetic reprogrammable coding-metasurface holograms
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Di, B., Zhang, H., Song, L., Li, Y., Han, Z., & Poor, H. V. (2020) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.3000813 · Cited by 544
Self-citationSmart metasurface with self-adaptively reprogrammable functions
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Self-citationAn optically driven digital metasurface for programming electromagnetic functions
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Self-citationLiquid crystal programmable metasurface for terahertz beam steering
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Empowering Metasurfaces with Inverse Design: Principles and Applications
Li, Z., Pestourie, R., Lin, Z., Johnson, S. G., & Capasso, F. (2022) · ACS Photonics · doi:10.1021/acsphotonics.1c01850 · Cited by 283
“118 It opens a new paradigm for intelligent surveillance, compressed sensing, and beyond.”
Background
Metadata
- Authors
- Li, L., Ruan, H., Liu, C., Li, Y., Shuang, Y., Alù, A., Qiu, C.-W., & Cui, T. J.
- Venue
- Nature Communications
- Published
- 2019-03-06
- Volume
- 10
- Issue
- 1
- Pages
- 1082-1082
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W2919338369
- Cited by
- 592
- References
- 31
- FWCI
- 23.80
- Type
- journal article
- Language
- en
- Open access
- gold
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