Hair Disease Classification Using Convolutional Neural Network Algorithm with VGG-16 Architecture

    October 2023 in “ Sinkron ”
    Ichwanul Muslim Karo Karo, Dedi Kiswanto, Suvriadi Panggabean, Adidtya Perdana
    Studysummary This study demonstrated that a CNN-based model using VGG-16 architecture achieved a 94.5% accuracy in classifying ten types of hair diseases, implying a promising tool for aiding health professionals in diagnosing hair conditions accurately.
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