research Automated Skin Surface Phenotype for Melanoma Risk Assessment
An automated method accurately assesses melanoma risk using 3D body images to analyze skin traits.
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research Convolutional Neural Networks for Non-Invasive Diagnosis of Androgenetic Alopecia Using Dermoscopic Hair Images
Deep learning can improve non-invasive alopecia diagnosis using hair images.
research Predicting Hair Loss With AI: A Deep Learning Framework Combining Genetic And Scalp Health Data
This study presents a deep learning framework that predicts hair loss by integrating genetic, hormonal, scalp health, and lifestyle data. Convolutional Neural Networks (CNNs) are used to extract features from high-resolution scalp images, identifying thinning patterns and follicle health. Recurrent Neural Networks (RNNs), particularly Long Short-Term Memory (LSTM) networks, model temporal sequences of lifestyle and health data to capture longitudinal patterns in hair loss progression. This approach aims to enhance the understanding and prediction of hair loss by combining diverse data sources.
research NLKFill: High-Resolution Image Inpainting With a Novel Large Kernel Attention
NLKFill improves high-resolution image inpainting by effectively capturing image details and enhancing speed.
research Hair Tone Estimation at Roots via Imaging Device with Embedded Deep Learning
The device accurately estimates natural hair color at the roots in real time.
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