research Pre-trained classification of scalp conditions using image processing
The system can automatically classify scalp conditions with 85% accuracy.
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30 / 1000+ resultsresearch Prediction of Alopecia Areata using CNN
A new CNN model can detect Alopecia Areata with 98% accuracy.
research Hair Disease Classification Using Convolutional Neural Network (CNN) Algorithm with VGG-16 Architecture
The system can accurately classify hair diseases with 94.5% accuracy using a CNN.
research Using morphological operators and inpainting for hair removal in dermoscopic images
The new algorithm removes hair from skin images better than previous methods, helping diagnose melanoma.
research Multi-Class Support Vector Machine Classification for Detecting Alopecia Areata and Scalp Diseases
The method accurately detects and classifies scalp diseases, including alopecia areata, with 89.3% accuracy.
research Automated quantitative analysis of coat and skin coloration in laboratory animals
A new algorithm accurately analyzes animal coat and skin colors quickly and easily.
research Application of 3D Reflectance Confocal Microscopy: Melanocytic Proliferations as 3D Models; JAAD Supplemental Material
3D models from confocal microscopy improve melanoma detection on sun-damaged skin.
research Optimized VGG19 Architecture for Precise and Efficient Multi-Class Hair Disease Classification
The optimized VGG19 model accurately classifies hair diseases with 98.64% accuracy.
research BaldPredict: AI-Driven Prediction Model for Alopecia Areata
AI can improve alopecia areata diagnosis with high accuracy.
research A Comprehensive Survey on Vitiligo Detection Using Deep Learning
Better datasets and methods are needed for reliable vitiligo detection using deep learning.
research DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
research Hair cluster detection model based on dermoscopic images
The new model detects hair clusters more accurately and efficiently, helping with early hair loss treatment and diagnosis.
research An Improved Face Image Restoration Method Based on Denoising Diffusion Probabilistic Models
The new method improves facial image restoration quality and face recognition accuracy.
research MSF-VMDNet for multi class segmentation of skin cancer whole slide images using a multi frequency dual encoder network
MSF-VMDNet accurately segments skin cancer images better than existing methods.
research Hair & Scalp Disease Detection Using Machine Learning & Image Processing
AI can accurately diagnose hair and scalp conditions and suggest treatments.
research Trichoscopy of Alopecia Areata: Hair Loss Feature Extraction and Computation Using Grid Line Selection and Eigenvalue
Researchers developed an algorithm for self-diagnosing scalp conditions with high accuracy using smart device-attached microscopes.
research Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review
Computer vision techniques can help detect and assess skin conditions like vitiligo, alopecia areata, and dermatitis.
research ScalpEye: A Deep Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health
ScalpEye accurately diagnoses scalp issues like dandruff and hair loss.
research Optimizing skin disease diagnosis: harnessing online community data with contrastive learning and clustering techniques
Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
research Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions
Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
research Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets
The new method improves skin cancer detection in imbalanced datasets.
research Generative adversarial networks for anonymous acneic face dataset generation
The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.
research Hair and Scalp Disease Detection using Machine Learning and Image Processing
The machine learning model accurately detected hair loss and scalp diseases using processed images.
research Automating Hair Loss Labels for Universally Scoring Alopecia From Images
The AI system HairComb accurately scores hair loss severity, matching dermatologist assessments.
research The impact of alopecia areata on patients' daily lives: A study using social media in France
Alopecia areata significantly affects patients' lives, causing physical, psychological, social, and financial challenges.
research Flow-guided hair removal for automated skin lesion identification
The new method removes hair from skin images quickly and accurately to help identify skin lesions better.
research Book Reviews
The reviews critique three psychology books, noting skepticism about a personality inventory for teens, praising a practical guide on body image issues, and recommending a book on grief therapy.
research A Novel Fusion Technique for Early Detection of Alopecia Areata Using ResNet-50 and CRSHOG
AlopeciaDet accurately detects Alopecia Areata early using advanced image analysis.
research Detection of Meibomian Gland Dysfunction by in vivo Confocal Microscopy Based on Deep Convolutional Neural Network
The model can effectively help diagnose meibomian gland dysfunction automatically.
research A Combinatorial Tweet Clustering Methodology Utilizing Inter and Intra Cosine Similarity
The method effectively grouped tweets into categories without knowing the number of groups beforehand.