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Research progress in optical neural networks: theory, applications and developments

Jia Liu,  Qiuhao Wu,  Xiubao Sui,  Qian Chen,  Guohua Gu,  Liping Wang,  Shengcai Li

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Jia Liu, Qiuhao Wu, Xiubao Sui, Qian Chen, Guohua Gu, Liping Wang, Shengcai Li. Research progress in optical neural networks: theory, applications and developments[J]. PhotoniX. doi: 10.1186/s43074-021-00026-0
引用本文: Jia Liu, Qiuhao Wu, Xiubao Sui, Qian Chen, Guohua Gu, Liping Wang, Shengcai Li. Research progress in optical neural networks: theory, applications and developments[J]. PhotoniX. doi: 10.1186/s43074-021-00026-0
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Jia Liu, Qiuhao Wu, Xiubao Sui, Qian Chen, Guohua Gu, Liping Wang, Shengcai Li. Research progress in optical neural networks: theory, applications and developments[J]. PhotoniX. doi: 10.1186/s43074-021-00026-0
Citation: Jia Liu, Qiuhao Wu, Xiubao Sui, Qian Chen, Guohua Gu, Liping Wang, Shengcai Li. Research progress in optical neural networks: theory, applications and developments[J]. PhotoniX. doi: 10.1186/s43074-021-00026-0
shu

Research progress in optical neural networks: theory, applications and developments

doi: 10.1186/s43074-021-00026-0
基金项目: 

This work was supported in part by the National Natural Science Foundation of China under Grant 11773018 and Grant 61727802, in part by the Key Research and Development programs in Jiangsu China under Grant BE2018126, in part by the Fundamental Research Funds for the Central Universities under Grant 30919011401 and Grant 30920010001, and in part by the Leading Technology of Jiangsu Basic Research Plan under Grant BK20192003.

Research progress in optical neural networks: theory, applications and developments

  • 1.

    School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China

  • 2.

    Institute of Armored Forces, Army Research Institute, Beijing, China

Funds: 

This work was supported in part by the National Natural Science Foundation of China under Grant 11773018 and Grant 61727802, in part by the Key Research and Development programs in Jiangsu China under Grant BE2018126, in part by the Fundamental Research Funds for the Central Universities under Grant 30919011401 and Grant 30920010001, and in part by the Leading Technology of Jiangsu Basic Research Plan under Grant BK20192003.

    摘要
  • 摘要: With the advent of the era of big data, artificial intelligence has attracted continuous attention from all walks of life, and has been widely used in medical image analysis, molecular and material science, language recognition and other fields. As the basis of artificial intelligence, the research results of neural network are remarkable. However, due to the inherent defect that electrical signal is easily interfered and the processing speed is proportional to the energy loss, researchers have turned their attention to light, trying to build neural networks in the field of optics, making full use of the parallel processing ability of light to solve the problems of electronic neural networks. After continuous research and development, optical neural network has become the forefront of the world. Here, we mainly introduce the development of this field, summarize and compare some classical researches and algorithm theories, and look forward to the future of optical neural network.
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    Abstract: With the advent of the era of big data, artificial intelligence has attracted continuous attention from all walks of life, and has been widely used in medical image analysis, molecular and material science, language recognition and other fields. As the basis of artificial intelligence, the research results of neural network are remarkable. However, due to the inherent defect that electrical signal is easily interfered and the processing speed is proportional to the energy loss, researchers have turned their attention to light, trying to build neural networks in the field of optics, making full use of the parallel processing ability of light to solve the problems of electronic neural networks. After continuous research and development, optical neural network has become the forefront of the world. Here, we mainly introduce the development of this field, summarize and compare some classical researches and algorithm theories, and look forward to the future of optical neural network.
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  • 收稿日期:  2020-12-23
  • 录用日期:  2021-03-09
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