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Conferences > CLEO_QELS > 2021 > FTh1K > FTh1K.4

Deep learning-based spectral reconstruction on a chip using a scalable plasmonic encoder

Artem Goncharov, Calvin Brown, Zachary Ballard, Mason Fordham, Ashley Clemens, Yunzhe Qiu, Yair Rivenson, and Aydogan Ozcan

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Abstract

We demonstrate a deep learning-based spectroscopy framework using a low-cost on-chip plasmonic encoder. When blindly tested on N=14,648 random spectra our system shows competitive performance, where the reconstruction of an unknown spectrum on average takes ~28µs.

© 2021 The Author(s)

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