Optimized VGG19 Architecture for Precise and Efficient Multi-Class Hair Disease Classification
December 2024
New to Alopecia Areata? There is a guide in the encyclopedia. Read the guide → Studysummary In this study, a deep learning model using an optimized VGG19 architecture achieved a high classification accuracy of 98.64% for detecting ten hair disease classes from a balanced dataset, indicating its potential for reliable use in mobile diagnostics for clinical and remote applications.
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