Machine-learning reprogrammable metasurface imager

Nature Communications - Tập 10 Số 1
Lianlin Li1, Hengxin Ruan1, Che Liu2, Ying Li3, Ya Shuang1, Andrea Alù4, Cheng‐Wei Qiu3, Tie Jun Cui2
1State Key Laboratory of Advanced Optical Communication Systems and Networks, Department of Electronics, Peking University, 100871, Beijing, China
2State Key Laboratory of Millimeter Waves, Southeast University, 210096, Nanjing, China
3Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117583, Singapore
4Photonics Initiative, Advanced Science Research Center, City University of New York, 85 St. Nicholas Terrace, New York, NY, 10031, USA

Tóm tắt

AbstractConventional 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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Tập 10 Số 1

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