research Methods of Transfer Learning for Multiclass Hair Disease Categorization
Transfer learning with three neural network architectures accurately classifies hair diseases.
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research Harnessing Deep Learning for Scalp and Hair Disease Classification: A Comparative Study of Convolutional Neural Network Architectures
VGG16 and VGG19 are the most accurate for classifying scalp and hair diseases.
research Leveraging Deep Neural Networks to Uncover Unprecedented Levels of Precision in the Diagnosis of Hair and Scalp Disorders
A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.
research KEBOT: An Artificial Intelligence Based Comprehensive Analysis System for FUE Based Hair Transplantation
The KEBOT system is a highly accurate AI tool for analyzing hair transplants.
research Deep Clustering via Center-Oriented Margin-Free Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets
The new method improves skin cancer detection in imbalanced datasets.
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