AI-based content filtering system using an age prediction algorithm

Computer vision mainly focuses on the automatic extraction, analysis, and understanding of useful information from a single image or video. On the other hand, authenticity is emerging as one of the primary requirements in today's world by developing a system for computer vision complexity. Generally, two robust techniques such as age estimation and face recognition are required to maintain authenticity. In reality, fraud and scams are getting increased, so here this paper has proposed a new combined model for face recognition and age prediction. Face recognition has been implemented and presented in this paper by using a Deep Neural Network. The authenticity problem can be handled by using either facial recognition or age prediction alone; this study has presented a method that employs both of them together to enhance the system's robustness. So, first, this model detects the person's face, and then it predicts the person's age. If the individual is eligible to view the information or perform a task, their access will be limited; otherwise, their access will be restricted. So it helps to solve two difficulties in this case: the person's identification cannot be faked, and their age is also confirmed by the system. (CNN for the face, and mention technique for the age.)