Abstract
The perception of beauty whether applied to a face or any similar subject, differs among people, with assorted values doled out to magnificence levels or positions. Facial beauty assessment has gained significant interest in various domains, including cosmetics, image processing, and artificial intelligence. This review digs into facial beauty prediction utilizing the Attribute Aware Convolutional Neural Network (AACNN) according to the SCUT-FBP5500 benchmark dataset. The study in this paper closes by accentuating the requirement for more comprehensive and adjusted datasets and proposes future exploration bearings to improve model decency and address moral ramifications.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Ranah Research : Journal of Multidisciplinary Research and Development
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
