Oversampling Facial Motion Features Using the Variational Autoencoder to Estimate Oro-facial Dysfunction Severity

• Main Authors: Ipapo, Trassandra Jewelle, Del Rosario, Charlize, Alampay, Raphael, Abu, Patricia Angela R
• Format: text
• Published: Archīum Ateneo 2023
• Subjects: class imbalance; oro-facial dysfunction; oversampling; variational autoencoder; Computer Engineering; Electrical and Computer Engineering; Engineering
• Online Access: https://archium.ateneo.edu/discs-faculty-pubs/391; https://doi.ieeecomputersociety.org/10.1109/CGIP58526.2023.00013
• Institution: Ateneo De Manila University

Class imbalance, which negatively affects classification model performance, is a common problem with machine learning. Various oversampling methods have been developed as potential solutions to compensate for imbalanced data. SMOTE is one of the more common methods employed. However, deep generative...