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    Evaluation of Automated Measurement of Hair Density Using Deep Neural Networks

    January 2022 in “ Sensors
    Minki Kim, Sunwon Kang, Byoung-Dai Lee
    Studysummary This study analyzed deep learning's application to automate hair density measurement in images and found that YOLOv4 had the best performance among tested algorithms, with a mean average precision of 58.67.
    Automatically generated from the study's abstract, not written by a person, and not a review of the full paper. Not medical advice or a treatment recommendation. Read the original study, and consult a qualified healthcare professional before changing treatment. Full disclaimer
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    Research cited in this study 3

    1. Hair Transplantation: Basic Overview Journal of The American Academy of Dermatology · 2021
    2. ScalpEye: A Deep Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health IEEE Access · 2020
    3. Follicular Unit Extraction: A Minimally Invasive Hair Transplantation Method Dermatologic Surgery · 2002