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Tensorflow人脸识别系统设计 被引量:1

Design of Tensorflow Face Recognition System
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摘要 人脸识别是近几年深度学习的典型代表,Tensorflow这个深度学习平台通过卷积神经网络能够有效的学习和训练进而达到识别人脸,系统采用OpenCV中的Haar-like人脸识别分类器由OpenCV和Tensorflow相互结合搭建。能有效的捕捉人脸,并通过深度学习对人脸进行分类。 Face recognition is a typical representative of deep learning in recent years.Tensorflow,a deep learning platform,can effectively learn and train through convolutional neural networks to achieve face recognition.This system uses Haar-like face recognition classification in OpenCV.The device is built by combining OpenCV and Tensorflow.Can effectively capture human faces and classify human faces through deep learning.
作者 吴晶 赵厚科 WU Jing;ZHAO Hou-ke(Northeast Petroleum University Qinhuangdao,Hebei 066004,China;College of Electrical Information Engineering,Southwest Minzu University,Chengdu 610225,China)
出处 《佳木斯大学学报(自然科学版)》 CAS 2020年第4期54-58,共5页 Journal of Jiamusi University:Natural Science Edition
基金 教育部产学合作协同育人项目(201801264014) 黑龙江省教育厅十三五教育规划课题(GZB1318001) 东北石油大学青年科学基金项目(2018QNQ-09) 东北石油大学青年科学基金项目(2018QNQ-08) 秦皇岛科技局项目(201902A004)。
关键词 深度学习 人脸识别 卷积神经网路 OPENCV tensorflow deep learning face recognition convolutional neural network OpenCV Tensorflow
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