research Boundary-Aware Multi-Stage with Mobile U-Net for Hair Segmentation in Dermoscopic Images
The new method improves hair segmentation in skin images, helping detect skin cancer more accurately.
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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 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 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 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.
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