Intelligent University Identity Identification System Based on FaceNet and FSRNet

University identification is one of the important ways to ensure the security management of today’s open campus. It can effectively detect and identify the suspicious person’s identity and ensure the security of the university campus. However, traditional university identity recognition systems have slow detection speeds, relatively low recognition rates, and inability to process low-resolution images. In view of the above problems, this paper proposes a university identity recognition system based on FaceNet and FSRNet. Combining virtual sample generation technology, face rectification algorithm, and improved MTCNN face detection. It effectively improves performance indicators such as detection speed and recognition rate, and provides solutions for low-resolution face images. The experimental results show that compared with the traditional university identity recognition system, the implementation method proposed in this paper improves the recognition rate of unconstrained natural environment by 1–2%, reduces the system face detection time, and effectively resolves low-resolution Facial face image for information restoration.