Employing DL-Based Algorithm for Gender and Age Identification

Age and gender prediction with deep learning is a field of emerging practical application importance and influence in research. Because deep learning can extract complex characteristics from visual data, it has revolutionized and is still revolutionizing age and gender prediction models, particularly when it comes to Convolutional Neural Networks (CNN), ResNet50, and Vgg16. This paper provides an overview view of recent advances and techniques within this field, in a way, pointing towards the central role played by deep learning architectures, data preprocessing technique, and transfer learning. Large as well as diverse datasets (UTKFace) are found to provide advanced results on developing hybrid models in this work. It also raises issues of redundancy, privacy concerns and potential bias as well, hence the development of AI needs to be done responsibly.