Journal of Optoelectronics · Laser, Volume. 35, Issue 8, 880(2024)

Keratoconus classification algorithm based on incremental learning

LAI Yuqing1, LIU Fenglian1, LI Jing1, WANG Riwei2, and TAN Zuoping2、*
Author Affiliations
  • 1Key Laboratory on Computer Vision and Systems, Ministry of Education of China, Tianjin Key Laboratory on Intelligence Computing and Novel Software Technology, Tianjin University of Technology, Tianjin 300384, China
  • 2Zhejiang Women's Science and Technology Innovation Studios, Wenzhou University of Technology, Wenzhou, Zhejiang 325035, China
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    References(10)

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    [2] [2] SHARIF R, BAK-NIELSEN S, HJORTDAL J, et al. Pathogenesis of keratoconus: the intriguing therapeutic potential of prolactin-inducible protein[J]. Progress in Retinal and Eye Research, 2018, 67:150-167.

    [4] [4] ATALAY E, ZALP O, YILDIRIM N. Advances in the diagnosis and treatment of keratoconus[J]. Therapeutic Advances in Ophthalmology, 2021, 13: 25158414211012796.

    [5] [5] VINCIGUERRA R, AMBRSIO JR R, ROBERTS C J, et al. Biomechanical characterization of subclinical keratoconus without topographic or tomographic abnormalities[J]. Journal of Refractive Surgery, 2017, 33(6): 399-407.

    [10] [10] LAVRIC A, POPA V, TAKAHASHI H, et al. Detecting keratoconus from corneal imaging data using machine learning[J]. IEEE Access, 2020, 8:149113-149121.

    [12] [12] KIM D, HAN B. On the stability-plasticity dilemma of class-incremental learning[C] //IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-22, 2023, Vancouver, Canada. New York: IEEE, 2023: 20196-20204.

    [13] [13] POLIKAR R, UPDA L, UPDA S S, et al. Learn++: an incremental learning algorithm for supervised neural networks[J]. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 2001, 31(4): 497-508.

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    [15] [15] SONY S A, ZAMAN T, ISLAM M K, et al. eLearn++: An effective incremental learning approach for brain tumor detection[C]//2021 2nd International Conference for Emerging Technology(INCET), May 21-23, 2021, Belagavi, India. New York: IEEE, 2021:1-8.

    [18] [18] WANG L, WU C. Dynamic imbalanced business credit evaluation based on Learn++ with sliding time window and weight sampling and FCM with multiple kernels[J]. Information Sciences, 2020, 520: 305-323.

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    LAI Yuqing, LIU Fenglian, LI Jing, WANG Riwei, TAN Zuoping. Keratoconus classification algorithm based on incremental learning[J]. Journal of Optoelectronics · Laser, 2024, 35(8): 880

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    Paper Information

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    Received: Aug. 16, 2023

    Accepted: Dec. 13, 2024

    Published Online: Dec. 13, 2024

    The Author Email: TAN Zuoping (tanzp@wzu.edu.cn)

    DOI:10.16136/j.joel.2024.08.0437

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