Methods of Transfer Learning for Multiclass Hair Disease Categorization

    December 2023
    Sheshang Degadwala, Dhairya Vyas, Pooja Mitra … Suvra Mandal
    Studysummary This study found that applying transfer learning with CNN architectures like AlexNet, VGG16, and ResNet50 achieved 99% accuracy in classifying multiclass hair disorders, suggesting a potential technological aid for dermatologists in diagnosing and treating hair conditions.
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