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Research 30 of 34
- 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
- A Machine Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health
- An Approach to Detect Alopecia Areata Hair Disease Using Deep Learning
- 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
- Scalp disease analysis using deep learning models
- Hair Disease Classification Using Convolutional Neural Network (CNN) Algorithm with VGG-16 Architecture
- Hair & Scalp Disease Detection Using Machine Learning & Image Processing
- Artificial neural networks algorithms for prediction of human hair loss related autoimmune disorder problem
- Editorial: Progress and Prospects on Skin Imaging Technology, Teledermatology and Artificial Intelligence in Dermatology
- Sample collecting methods for bacterial community structure analysis of scalp hair: non-invasive swabbing versus intrusive hair shaft cutting
- Skin aging: mechanisms, evaluation, and rejuvenation
- Scalp Disorder Imaging: How Deep Learning and Explainable Artificial Intelligence are Revolutionizing Diagnosis and Treatment
- ScalpEye: A Deep Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health
- Optimized polycystic ovarian disease prognosis and classification using AI based computational approaches on multi-modality data
- How good is artificial intelligence (AI) at solving hairy problems? A review of AI applications in hair restoration and hair disorders
- Quantitative analysis and development of alopecia areata classification frameworks
- BaldGraphFormer: An Explainable Deep Learning Framework for Early Baldness Prediction by Integrating Swin Transformer, Graph Attention Networks and Clinical Features
- Relationship between the bacterial community structures on human hair and scalp
- NLKFill: high-resolution image inpainting with a novel large kernel attention
- A Study on the Development of a Web Platform for Scalp Diagnosis Using EfficientNet
- Innovative approaches to baldness detection and management with artificial intelligence and machine learning
- A Novel Fusion Technique for Early Detection of Alopecia Areata Using ResNet-50 and CRSHOG
- Evaluation of Automated Measurement of Hair Density Using Deep Neural Networks
- Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review
- Hair Follicle Classification and Hair Loss Severity Estimation Using Mask R-CNN
- HairSentinel: a time-aware anomaly detection framework for forecasting hairfall trends using temporal fusion transformers