Yue, Yuanli, Liu, Shouju, Wang, Chao (2024) Reservoir computing assisted single-pixel high-throughput object classification. In: Proceedings Volume 12999, Optical Sensing and Detection VIII; 129992V (2024). SPIE (doi:10.1117/12.3022550) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:114441)
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| Official URL: https://doi.org/10.1117/12.3022550 |
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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.
| Item Type: | Conference proceeding |
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| DOI/Identification number: | 10.1117/12.3022550 |
| Uncontrolled keywords: | Reservoir computing, single-pixel detection, high throughput object recognition, structured illumination, line scanning |
| Subjects: | T Technology > TK Electrical engineering. Electronics. Nuclear engineering |
| Institutional Unit: | Schools > School of Engineering, Mathematics and Physics > Engineering |
| Former Institutional Unit: |
There are no former institutional units.
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| Depositing User: | Chao Wang |
| Date Deposited: | 06 May 2026 12:11 UTC |
| Last Modified: | 06 May 2026 12:11 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/114441 (The current URI for this page, for reference purposes) |
University of Kent Author Information
Wang, Chao.
| Creator's ORCID: |
 https://orcid.org/0000-0002-0454-8079
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