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    ARTICLE

    Deep Transfer Learning Models for Mobile-Based Ocular Disorder Identification on Retinal Images

    Roseline Oluwaseun Ogundokun1,2, Joseph Bamidele Awotunde3, Hakeem Babalola Akande4, Cheng-Chi Lee5,6,*, Agbotiname Lucky Imoize7,8

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 139-161, 2024, DOI:10.32604/cmc.2024.052153 - 18 July 2024

    Abstract Mobile technology is developing significantly. Mobile phone technologies have been integrated into the healthcare industry to help medical practitioners. Typically, computer vision models focus on image detection and classification issues. MobileNetV2 is a computer vision model that performs well on mobile devices, but it requires cloud services to process biometric image information and provide predictions to users. This leads to increased latency. Processing biometrics image datasets on mobile devices will make the prediction faster, but mobiles are resource-restricted devices in terms of storage, power, and computational speed. Hence, a model that is small in size,… More >

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