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Human action recognition using a time-delayed photonic reservoir computing

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Acknowledgements

This work was supported in part by National Natural Science Foundation of China (Grant Nos. 61927811, 62175177, U19A2076), Program for Guangdong Introducing Innovative and Entrepreneurial Teams, and Natural Science Foundation of Shanxi Province (Grant Nos. 201901D211116, 201901D211077).

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Authors and Affiliations

  1. Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan, 030024, China

    Chao Kai, Pu Li, Yi Yang & Bingjie Wang

  2. Guangdong Provincial Key Laboratory of Photonics Information Technology, School of Information Engineering, Guangzhou, 510006, China

    Pu Li & Yuncai Wang

  3. School of Computer Science and Electronic Engineering, Bangor University, Wales, LL57 1UT, UK

    K. Alan Shore

Authors
  1. Chao Kai
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  2. Pu Li
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  3. Yi Yang
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  4. Bingjie Wang
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  5. K. Alan Shore
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  6. Yuncai Wang
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Corresponding author

Correspondence to Pu Li.

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Appendixes A–C. The supporting information is available online at info.scichina.com and link.springer.com. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.

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Kai, C., Li, P., Yang, Y. et al. Human action recognition using a time-delayed photonic reservoir computing. Sci. China Inf. Sci. 66, 219401 (2023). https://doi.org/10.1007/s11432-022-3710-6

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  • DOI: https://doi.org/10.1007/s11432-022-3710-6

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