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Bald Men Dataset
Dataset comprises 3,100 images from 775 individuals, featuring male alopecia cases captured from two angles (front + top views) with corresponding segmentation masks. Designed for machine learning and deep learning models, this collection supports research in hair follicles analysis, hair density measurement, and scalp health evaluation.
By leveraging this dataset, researchers can improve learning algorithms for detecting hair disorders, evaluating hair restoration techniques, and training models for early diagnosis of alopecia. - Get the data
The inclusion of segmentation masks ensures accurate classification of hair textures, scalp conditions, and hair growth stages, making it invaluable for medical image analysis and AI-driven dermatology.
Frequently Asked Questions
Who can benefit from this men hair loss dataset?
The dataset can benefit dermatology researchers, medical-imaging teams, computer-vision engineers, and developers building hair-analysis applications. It can support research into hair density, scalp conditions, alopecia progression, and automated hair-loss assessment.
How do the segmentation masks help model development?
The masks provide pixel-level information about relevant hair and scalp regions, giving models more detailed supervision than image-level classification labels. This can help researchers estimate hair-covered versus exposed scalp areas, analyze hair density, and develop segmentation models for automated scalp analysis.
Does the dataset represent real individuals?
Yes. The source describes the collection as real-world imagery of men with different degrees of baldness and alopecia rather than synthetic images. The dataset was collected through crowdsourcing, providing naturally captured examples for computer-vision research.
💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at https://unidata.pro to discuss your requirements and pricing options.
Example for the dataset
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Each participant contributes 4 images (original + mask pairs), enabling precise diagnosis of hair loss, hair thinning patterns, and treatment personalization.
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