Image recognition based on optical reservoir computing

Jiayi Li; Qiang Cai; Pu Li; Yi Yang; K. Alan Shore; Yuncai Wang

doi:10.1063/5.0110838

Image recognition based on optical reservoir computing

Jiayi Li
, Qiang Cai
, Pu Li
, Yi Yang
, K. Alan Shore
, Yuncai Wang

Ysgol Cyfrifiadureg a Pheirianneg

Taiyuan University of Technology
Guangdong University of Technology

Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid

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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.

Iaith wreiddiol	Saesneg
Rhif yr erthygl	123106
Cyfnodolyn	Chaos: An Interdisciplinary Journal of Nonlinear Science
Cyfrol	32
Rhif cyhoeddi	12
Dyddiad ar-lein cynnar	1 Rhag 2022
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1063/5.0110838
Statws	Cyhoeddwyd - Rhag 2022

Mynediad at Ddogfen

10.1063/5.0110838

Dyfynnu hyn

@article{a610f20c94b44bf7aa156b851be32ce6,

title = "Image recognition based on optical reservoir computing",

abstract = "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\textbackslash{} this scheme may provide a resource-efficient alternative approach to image recognition.",

author = "Jiayi Li and Qiang Cai and Pu Li and Yi Yang and \{Alan Shore\}, K. and Yuncai Wang",

year = "2022",

month = dec,

doi = "10.1063/5.0110838",

language = "English",

volume = "32",

journal = "Chaos: An Interdisciplinary Journal of Nonlinear Science",

issn = "1054-1500",

publisher = "American Institute of Physics",

number = "12",

}

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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

SN - 1054-1500

VL - 32

JO - Chaos: An Interdisciplinary Journal of Nonlinear Science

JF - Chaos: An Interdisciplinary Journal of Nonlinear Science

IS - 12

M1 - 123106

ER -

Image recognition based on optical reservoir computing

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