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- Deep Learning Approaches for Hair Disease Classification: A Comparative Analysis of MobileNetV2 and VGG19 Architectures
- Optimized VGG19 Architecture for Precise and Efficient Multi-Class Hair Disease Classification
- Harnessing Deep Learning for Scalp and Hair Disease Classification: A Comparative Study of Convolutional Neural Networks Architectures
- Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders
- HairLossMultinet: A Multi Scale Feature Fusion Method Using Deep Learning Approach
- Investigating Different Deep learning Models for Classification of Folliculitis
- A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
- A Machine Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health
- Methods of Transfer Learning for Multiclass Hair Disease Categorization
- An Approach to Detect Alopecia Areata Hair Disease Using Deep Learning
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