Optical Instruments, Volume. 42, Issue 5, 33(2020)

Identifying diabetic retinopathy based on deep transfer learning

Yuming YAN, Feng LI*, Deming LUO, Siyuan YIN, Xiaotian FU, Zheng LIU, and Lei YAN
Author Affiliations
  • School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
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    References(14)

    [2] [2] STEWART M. Diabetic retinopathy: current pharmacologic treatment emerging strategies[M]. Singape: Springer, 2017.

    [5] [5] LI H Q, CHUTATAPE O. Fundus image features extraction[C]Proceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine Biology Society. Chicago, USA: IEEE, 2000: 3071 3073.

    [6] [6] HALOI M. Improved microaneurysm detection using deep neural wks[J]. arXiv: 1505.04424, 2015.

    [10] [10] KRIZHEVSKY A, SUTSKEVER I, HINTON G E. Image classification with deep convolutional neural wks[C]Proceedings of the 25th International Conference on Neural Infmation Processing Systems. Lake Tahoe, Nevada: ACM, 2012: 19.

    [11] BOOTH D E. The cross-entropy method[J]. Technometrics, 50, 92(2008).

    [14] SOLANKI K, BHASKARANAND M, RAMACHANDRA C. Clinical validation study of an automated DR screening system using color fundus images against 7-field ETDRS stereoscopic reference standard[J]. EURETINA(2016).

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    Yuming YAN, Feng LI, Deming LUO, Siyuan YIN, Xiaotian FU, Zheng LIU, Lei YAN. Identifying diabetic retinopathy based on deep transfer learning[J]. Optical Instruments, 2020, 42(5): 33

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    Paper Information

    Category: APPLICATION TECHNOLOGY

    Received: Mar. 26, 2020

    Accepted: --

    Published Online: Jan. 6, 2021

    The Author Email: LI Feng (lifenggold@163.com)

    DOI:10.3969/j.issn.1005-5630.2020.05.006

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