Automatic Grading of Palsy Using Asymmetrical Facial Features: A Study Complemented by New Solutions

Automatic Grading of Palsy Using Asymmetrical Facial Features: A Study Complemented by New Solutions

Facial palsy caused by nerve damage results in loss of facial symmetry and expression. A reliable palsy grading system for large-scale applications is still missing in the literature. Although numerous approaches have been reported on facial palsy quantification and grading, most employ hand-crafted...

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Bibliographic Details
Main Authors: Muhammad Sajid, Tamoor Shafique, Mirza Jabbar Aziz Baig, Imran Riaz, Shahid Amin, Sohaib Manzoor
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:Symmetry
Subjects:
convolutional neural networks
facial palsy grading
datasets
generative adversial networks
primary health care
Online Access:http://www.mdpi.com/2073-8994/10/7/242

Internet

http://www.mdpi.com/2073-8994/10/7/242

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