Hardware AI-empowered ultrasensitive detection

Qizhou Wang; Ning Li; Zhao He; Arturo Burguete Lopez; Maksim Makarenko; Fei Xiang; Andrea Fratalocchi

doi:10.1117/12.3009163

18 June 2024 Hardware AI-empowered ultrasensitive detection

Qizhou Wang, Ning Li, Zhao He, Arturo Burguete Lopez, Maksim Makarenko, Fei Xiang, Andrea Fratalocchi

Proceedings Volume 13017, Machine Learning in Photonics; 1301704 (2024) https://doi.org/10.1117/12.3009163
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

This work proposed a universal platform for ultra-sensitive detection, which integrates sensory data acquisition and spectral feature extraction into a single machine learning (ML) hardware.We fabricated and tested the sensing platform in glucose detection tasks, reaching 5 orders of magnitude higher sensitivity compared to the state-of-the-art. This technology requires no bulky spectral measuring devices such as a spectrum analyzer but a standard off-the-shelf camera to achieve real-time detection of the glucose concentration.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qizhou Wang, Ning Li, Zhao He, Arturo Burguete Lopez, Maksim Makarenko, Fei Xiang, and Andrea Fratalocchi "Hardware AI-empowered ultrasensitive detection", Proc. SPIE 13017, Machine Learning in Photonics, 1301704 (18 June 2024); https://doi.org/10.1117/12.3009163

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