Facial Recognition Based on Convolutional Neural Networks
Facial recognition is an important technology in the field of computer vision,with a wide range of application scenarios,such as security monitoring,identity verification,social networks,etc.This article proposes a face recognition model based on Convolutional Neural Networks(CNN)using deep learning tech-niques,which achieves high-precision recognition of faces by training a large amount of data.This article first provides a detailed description of the design and implementation process of a convolutional neural network model.Then,the ReLU activation function was used to increase the nonlinearity of the model,and the back-propagation algorithm was used for practical training.Finally,the model was trained and tested on a publicly available facial dataset,achieving a 100％accuracy rate.The experimental results show that the model ex-hibits excellent performance in recognition rate,robustness,and generalization ability.
万方数据
维普
