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Research 12
- Deep Learning Approaches for Hair Disease Classification: A Comparative Analysis of MobileNetV2 and VGG19 Architectures
- Scalp Disease Detection Using Deep Learning: A Hybrid Ensemble Approach with EfficientNetB0, DenseNet121 and MobileNetV2
- A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
- Scalp disease analysis using deep learning models
- Generative adversarial networks for anonymous acneic face dataset generation
- Hair cluster detection model based on dermoscopic images
- Diagnosis of Scalp Disorders using Machine Learning and Deep Learning Approach -- A Review
- Weakly-Supervised Hair SEM Microscope Image Segmentation Using a Priori Structure Information
- Advances in Digital Light Processing (DLP) Bioprinting: A Review of Biomaterials and Its Applications, Innovations, Challenges, and Future Perspectives
- Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders
- An Early Hair Loss Detection and Prediction Method Based on Machine Learning
- Deep Learning-based Trichoscopic Image Analysis and Quantitative Model for Predicting Basic and Specific Classification in Male Androgenetic Alopecia