Age and Gender Prediction from Facial Images Using Deep Learning Approach
Authors:-Associate Professor Dr. A. Selva Reegan, Adan C Benedict, Jeevithan S, Hari B L, Raghul Babu J
Abstract- significant attention due to its wide range of applications in various facial investigations. This research paper presents a comprehensive approach utilizing convolutional neural networks (CNN) and deep learning methodologies to develop a gender and age detection system. The paper explores the underlying algorithms and techniques employed in CNN models for gender classification and age estimation, highlighting their synergy and integration. The primary objective of this study is to leverage deep learning techniques to create an accurate gende and age detector capable of providing approximate predictions for human faces in images. Additionally, the paper discusses the significance of this technology and its potential impact on improving everyday lives. Further- more, the research paper emphasizes the diverse range of applications where such technology can be effectively utilized. These applications span across various domains, including intelligence agencies, CCTV cameras, policing, and matrimony websites. The potential benefits and implications of implementing gender and age detection systems in these areas are explored. Overall, this research paper provides insights into the development of a gender and age detection system using deep learning and highlights its potential applications in different sectors, showcasing the value and impact it can have on society .]Automatic age and gender prediction from facial images has gained significant attention due to its wide range of applications in various facial investigations. This research paper presents a comprehensive approach utilizing convolutional neural networks (CNN) and deep learning methodologies to develop a gender and age detection system. The paper explores the underlying algorithms and techniques employed in CNN models for gender classification and age estimation, highlighting their synergy and integration. The primary objective of this study is to leverage deep learning techniques to create an accurate gender and age detector capable of providing approximate predictions for human faces in images. Additionally, the paper discusses the significance of this technology and its potential impact on improving everyday lives. Further- more, the research paper emphasizes the diverse range of applications where such technology can be effectively utilized. These applications span across various domains, including intelligence agencies, CCTV cameras, policing, and matrimony websites. The potential benefits and implications of implementing gender and age detection systems in these areas are explored. Overall, this research paper provides insights into the development of a gender and age detection system using deep learning and highlights its potential applications in different sectors, showcasing the value and impact it can have on society .
