Developing an artificial intelligence-based progressive growing GAN for high-quality facial profile generation and evaluation through turing test and aesthetic analysis

Developing an artificial intelligence-based progressive growing GAN for high-quality facial profile generation and evaluation through turing test and aesthetic analysis

Abstract This study aimed to develop a Progressive Growing Generative Adversarial Network with Gradient Penalty (WPGGAN-GP) to generate high-quality facial profile images, addressing the scarcity of diverse training data in orthodontics. A dataset of 50,000 profile images, representing varied ages,...

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Bibliographic Details
Main Authors: Shahab Kavousinejad, Kazem Dalaie, Mohammad Behnaz, Soodeh Tahmasbi, Asghar Ebadifar, Hoori Mirmohammadsadeghi
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Artificial intelligence
Orthodontics
Deep learning
Image processing
Online Access:https://doi.org/10.1038/s41598-025-11172-x
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https://doi.org/10.1038/s41598-025-11172-x

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