Design and implementation of anti-cheating face verification system based on big data analysis
With the widespread use of facial recognition technology,spoofing attacks,such as using photos,videos,or 3D masks to mimic legitimate users,research on anti-spoofing technology can significantly improve the security of facial verification systems.This system is an attack detection system based on convolutional neural networks.By performing face detection on images based on the MTCNN architecture under PAD,a perfect separation method between reality and attack is proposed in the Replay Mobile dataset.The intelligent public storage cabinet face recognition system is applied and designed to achieve safe use of face recognition technology in unmanned situations and good performance in the protocol of the dataset.
information securityface recognitiondeep learninggenerative adversarial networkliving body detection
万方数据
维普
