摘要
Abstract
Facial recognition technology is a biometric recognition technology based on machine learning,which identifies individual identity by analyzing facial features.This technology has wide application value in many fields such as security,finance,transportation,and entertainment,and can improve the accuracy and convenience of identity verification,protect personal privacy and public safety.In this background,this paper implements a facial recognition system developed using machine learning.Throughout the development of the entire system,the main technologies used in facial recognition are the TensorFlow framework of machine learning and VGGNet.The entire facial recognition is divided into three steps.First of all,the preprocessing of image data information needs to be completed,and the algorithm parameters need to be managed.Subsequently,the VGGNet algorithm needs to be used to complete the recognition and operation of the face.After the facial recognition system is implemented,it is analyzed and tested to determine whether the system's performance can meet the overall processing requirements.关键词
人脸识别/VGGNet模型/机器学习/TensorFlowKey words
facial recognition/VGGNet mode/deep learning/TensorFlow分类
信息技术与安全科学
