REGRESSION AND CLASSIFICATION MODELS FOR HUMAN AGE PREDICTION - Patil, Bhuvaneshwari; Rumma, Shivanand S.; Hangarge, Mallikarjun (LPPM Universitas Jambi, 2024)
This study aims to enhance automated age prediction from facial images, a task with significant potential in security, law enforcement, and Human-Computer Interaction (HCI). While age estimation has seen progress, it remains a challenging problem due to the diverse factors influencing facial aging, such as genetics, environment, lifestyle, and facial expressions. These variations result in individuals of the same chronological age looking markedly different. Most existing age estimation methods rely on computationally intensive pre-trained models, often treated as