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Communication Dans Un Congrès Année : 2019

Deep Learning based Detection of Hair Loss Levels from Facial Images

Résumé

Hair loss is a phenomenon known to affect people's morale and self-confidence. Often, the awareness of the phenomenon and the possibilities of treatment is late. This paper investigates deep learning methods for detecting hairs loss levels by men from face images. In this context, a specific training dataset has been prepared with face images having varied levels of baldness. Moreover, in spite of the low visibility of hairs in such images, a matching method is proposed for automatically classifying facial images with respect to pattern classification tables of male baldness from the medical area. Experimental results show the potential and the efficiency for medical, security and commercial applications.
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Dates et versions

hal-04054698 , version 1 (31-03-2023)

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Halim Benhabiles, Karim Hammoudi, Ziheng Yang, Feryal Windal, Mahmoud Melkemi, et al.. Deep Learning based Detection of Hair Loss Levels from Facial Images. 2019 Ninth International Conference on Image Processing Theory, Tools and Applications (IPTA), Nov 2019, Istanbul, Turkey. ⟨10.1109/IPTA.2019.8936122⟩. ⟨hal-04054698⟩
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