Face recognition framework based on effective computing and adversarial neural network and its implementation in machine vision for social robots

In recent years, with the continuous breakthrough of computer vision technology, the accuracy of object detection and target recognition has been improved by leaps and bounds. Face recognition is one of the important research directions in the field of computer vision, which is widely used in mobile payment, safe city, criminal investigation and other fields. Traditional face recognition methods need to extract face image features manually. The extracted features are greatly affected by subjective factors, and time-consuming and laborious. Deep learning is the most important technology in the field of computer vision at present. Compared with traditional face recognition methods, it can extract more essential features of face image without manual participation. In this paper, we build a face recognition system based on neural computing model and the principle of neural network. The experimental results show that the proposed method has high detection rate and short processing time.