Reservoir computing assisted single-pixel high-throughput object classification

Yuanli Yue; Shouju Liu; Chao Wang

doi:10.1117/12.3022550

20 June 2024 Reservoir computing assisted single-pixel high-throughput object classification

Yuanli Yue, Shouju Liu, Chao Wang

Proceedings Volume 12999, Optical Sensing and Detection VIII; 129992V (2024) https://doi.org/10.1117/12.3022550
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Conference Poster

Abstract

This paper introduces a novel approach to high-throughput moving target detection using reservoir computing, which is both proposed and experimentally demonstrated. The implementation involves utilizing a Digital Micromirror Device (DMD) to introduce selected patterns for spatial encoding. During the target detection stage, optical line scan is employed, and a single-pixel detector collects the transmitted signal. Reservoir Computing (RC) is employed to do target classification. Experimental results reveal that shapes of the moving objects can be effectively classified.

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

Citation Download Citation

Yuanli Yue, Shouju Liu, and Chao Wang "Reservoir computing assisted single-pixel high-throughput object classification", Proc. SPIE 12999, Optical Sensing and Detection VIII, 129992V (20 June 2024); https://doi.org/10.1117/12.3022550

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