Research Portal

Image recognition based on optical reservoir computing

Research output: Contribution to journal › Article › peer-review

Standard Standard

Image recognition based on optical reservoir computing. / Li, Jiayi; Cai, Qiang; Li, Pu et al.
In: Chaos: An Interdisciplinary Journal of Nonlinear Science, Vol. 32, No. 12, 123106, 12.2022.

Research output: Contribution to journal › Article › peer-review

HarvardHarvard

Li, J, Cai, Q, Li, P, Yang, Y, Alan Shore, K & Wang, Y 2022, 'Image recognition based on optical reservoir computing', Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 32, no. 12, 123106. https://doi.org/10.1063/5.0110838

APA

Li, J., Cai, Q., Li, P., Yang, Y., Alan Shore, K., & Wang, Y. (2022). Image recognition based on optical reservoir computing. Chaos: An Interdisciplinary Journal of Nonlinear Science, 32(12), Article 123106. https://doi.org/10.1063/5.0110838

CBE

Li J, Cai Q, Li P, Yang Y, Alan Shore K, Wang Y. 2022. Image recognition based on optical reservoir computing. Chaos: An Interdisciplinary Journal of Nonlinear Science. 32(12):Article 123106. https://doi.org/10.1063/5.0110838

MLA

Li, Jiayi et al. "Image recognition based on optical reservoir computing". Chaos: An Interdisciplinary Journal of Nonlinear Science. 2022. 32(12). https://doi.org/10.1063/5.0110838

VancouverVancouver

Li J, Cai Q, Li P, Yang Y, Alan Shore K, Wang Y. Image recognition based on optical reservoir computing. Chaos: An Interdisciplinary Journal of Nonlinear Science. 2022 Dec;32(12):123106. Epub 2022 Dec 1. doi: 10.1063/5.0110838

Author

Li, Jiayi ; Cai, Qiang ; Li, Pu et al. / Image recognition based on optical reservoir computing. In: Chaos: An Interdisciplinary Journal of Nonlinear Science. 2022 ; Vol. 32, No. 12.

RIS

TY - JOUR

T1 - Image recognition based on optical reservoir computing

AU - Li, Jiayi

AU - Cai, Qiang

AU - Li, Pu

AU - Yang, Yi

AU - Alan Shore, K.

AU - Wang, Yuncai

PY - 2022/12

Y1 - 2022/12

N2 - We propose an image recognition approach using a single physical node based optical reservoir computing. Specifically, an optically injected semiconductor laser with self-delayed feedback is used as the reservoir. We perform a handwritten-digit recognition task by greatly increasing the number of virtual nodes in delayed feedback using outputs from multiple delay times. Final simulation results confirm that the recognition accuracy can reach 99\ this scheme may provide a resource-efficient alternative approach to image recognition.

AB - We propose an image recognition approach using a single physical node based optical reservoir computing. Specifically, an optically injected semiconductor laser with self-delayed feedback is used as the reservoir. We perform a handwritten-digit recognition task by greatly increasing the number of virtual nodes in delayed feedback using outputs from multiple delay times. Final simulation results confirm that the recognition accuracy can reach 99\ this scheme may provide a resource-efficient alternative approach to image recognition.

U2 - 10.1063/5.0110838

DO - 10.1063/5.0110838

M3 - Article

VL - 32

JO - Chaos: An Interdisciplinary Journal of Nonlinear Science

JF - Chaos: An Interdisciplinary Journal of Nonlinear Science

SN - 1054-1500

IS - 12

M1 - 123106

ER -