Paper Contents
Abstract
This review paper explores recent advancements in age and gender estimation within the realm of facial recognition technology. The rapid evolution of computer vision and machine learning techniques has led to significant progress in accurately determining both age and gender from facial images. The paper begins by summarizing key findings from existing literature, highlighting the diverse range of methodologies employed, including traditional feature-based approaches and more contemporary deep learning models. A comprehensive analysis of benchmark datasets used for training and evaluation is presented, shedding light on the challenges and limitations associated with different datasets.
Copyright
Copyright © 2024 Venugopal D R. This is an open access article distributed under the Creative Commons Attribution License.
