Please use this identifier to cite or link to this item:
https://doi.org/10.1038/s41467-019-09103-2
Title: | Machine-learning reprogrammable metasurface imager | Authors: | Li, L. Ruan, H. Liu, C. Li, Y. Shuang, Y. Alù, A. Qiu, C.-W. Cui, T.J. |
Issue Date: | 2019 | Publisher: | Nature Publishing Group | Citation: | Li, L., Ruan, H., Liu, C., Li, Y., Shuang, Y., Alù, A., Qiu, C.-W., Cui, T.J. (2019). Machine-learning reprogrammable metasurface imager. Nature Communications 10 (1) : 1082. ScholarBank@NUS Repository. https://doi.org/10.1038/s41467-019-09103-2 | Rights: | Attribution 4.0 International | Abstract: | 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. © 2019, The Author(s). | Source Title: | Nature Communications | URI: | https://scholarbank.nus.edu.sg/handle/10635/209519 | ISSN: | 2041-1723 | DOI: | 10.1038/s41467-019-09103-2 | Rights: | Attribution 4.0 International |
Appears in Collections: | Staff Publications Elements |
Show full item record
Files in This Item:
File | Description | Size | Format | Access Settings | Version | |
---|---|---|---|---|---|---|
10_1038_s41467-019-09103-2.pdf | 2.15 MB | Adobe PDF | OPEN | None | View/Download |
This item is licensed under a Creative Commons License