| 基于深度卷积神经网络的人脸识别 |
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| 引用本文： | 刘楠,刘瑞安,尹宁浩,曾贝贝. 基于深度卷积神经网络的人脸识别[J]. 软件, 2019, 0(8): 6-8 |
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| 作者姓名： | 刘楠 刘瑞安 尹宁浩 曾贝贝 |
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| 作者单位： | 1.天津师范大学电子与通信工程学院 |
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| 基金项目： | 天津师范大学研究生科研实践创新应用项目(项目号:YZ1260021939) |
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| 摘 要： | 目前人脸识别技术被广泛应用于实际生活各个领域,尤其是在实时视频场景下应用越来越普及,因此对人脸识别的研究具有重大价值。通过应用Keras框架和深度学习相关知识构建深度卷积神经网络,训练出有效的人脸识别模型,并应用到实时视频场景进行人脸检测和识别,最后通过实验表明此方法能够有较高的正确率,并能准确识别视频中的人脸。
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| 关 键 词： | 人脸识别 卷积神经网络 深度学习 |
Face Recognition Based on Deep Convolutional Neural Network |
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| LIU Nan,LIU Rui-an,YIN Ning-hao,ZENG Bei-bei. Face Recognition Based on Deep Convolutional Neural Network[J]. Software, 2019, 0(8): 6-8 |
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| Authors: | LIU Nan LIU Rui-an YIN Ning-hao ZENG Bei-bei |
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| Affiliation: | (College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin 300387, China) |
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| Abstract: | At present, face recognition technology has great research value in various fields of society, especially in real-time video scenes. Deep convolutional neural network was built based on the deep learning related knowledge and the Keras framework to train an effective face recognition model, which was applied to real-time video scene for face detection and recognition. Finally, the experiment shows that this method has high accuracy and can identify faces in video accurately. |
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| Keywords: | Face recognition Convolutional neural network Deep learning |
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