research Scalp Disease Detection Using Deep Learning: A Hybrid Ensemble Approach with EfficientNetB0, DenseNet121 and MobileNetV2
The hybrid ensemble model improves scalp disease detection accuracy and consistency.
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5 / 25 resultsresearch A Study on the Development of a Web Platform for Scalp Diagnosis Using EfficientNet
A web platform was created to help diagnose scalp conditions accurately and easily.
research Automated Classification of Male and Female Pattern Hair Loss Stages Using EfficientNet According to the Hamilton-Norwood and Ludwig Scale
EfficientNet improves accuracy in diagnosing hair loss stages.
research A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
The system effectively detects scalp diseases and classifies hair fall stages with high precision.
research Classification of Visually Similar Scalp Diseases using Deep Learning: A Hybrid CNN-VIT Approach with Cross-Attention Fusion
ScalpViT accurately diagnoses similar-looking scalp diseases with 94.3% accuracy.
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