Machine Learning Approaches for Prediction of Facial Rejuvenation Using Real and Synthetic Data
This paper proposes a novel machine learning approaches to predict the outcome of facial rejuvenation prior to a cosmetic procedure. This is achieved by estimating the required amount of dermal filler volume that needs to be applied on the face by learning the underlying structural mapping from the...
Main Authors: | Syed Afaq Ali Shah, Mohammed Bennamoun, Michael K. Molton |
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Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8642338/ |
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