Design And Implementation Of Face Recognition System Based On Deep Learning

In recognition systems such as surveillance,the face pictures collected by the camera have low resolution due to the effects of distance,angle,and lighting,and exist in a variety of poses and forms,affecting the results of face image recognition.With the rapid development of monitoring,network transmission and other technologies in society in recent years,digital information has been far ahead of analog information,and more people prefer to use video acquisition,data compression,data analysis,and data access in the field of video surveillance.And other ways to process video information.Deep learning has developed rapidly in recent years.It is an emerging field in machine learning research.The concept of deep learning is derived from the study of artificial neural networks.It is a multi-layer perceptron with multiple hidden layers.It combines low-level features by combining Form a more abstract high-level representation attribute category or feature to discover the distributed feature representation of the data.In this paper,a face recognition system is developed.Based on the Le Net-5 convolutional neural network model,the model structure is improved,and the deep convolutional neural network is used to overcome the angle,pose,and light pair recognition during actual face recognition.The impact of the results,this paper uses Tensor Flow to build a deep convolutional neural network model,uses FERET,ORL,YALE face datasets and homemade face datasets for training,and finally uses Open CV for Python and other modules to implement the entire face recognition system.The system can realize the following functions: detection and recognition of human faces in pictures,and detection and recognition of human faces through cameras.Finally,the image was subjected to noise experiments to verify the performance of the system,and the function of outputting personal information after recognition was added.It can be used in corporate companies to search for basic information of employees by entering employee photos,and design and optimize the interface.