Face Image Scanning for Differentiation of Child/Adult images using a CNN-Based Model

Differentiating child and adult images is a crucial requirement for many applications. This paper proposes an approach using a Convolutional Neural Network (CNN) model to distinguish between children's images from adults. In contrast to predetermined face landmarks, the suggested approach learns complex face features and achieves 85% accuracy regardless of variation in age, gender, race, or ethnicity. The approach could be used to leverage the performance of digital image forensic, security control and, surveillance monitoring, and robotics.