A convolutional neural network based on TensorFlow for face recognition

Liping Yuan, Zhiyi Qu, Yufeng Zhao, Hongshuai Zhang, Qing Nian
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引用次数: 57

Abstract

Face recognition is a hot research field in computer vision, and it has a high practical value for the detection and recognition of specific sensitive characters. Research found that in traditional hand-crafted features, there are uncontrolled environments such as pose, facial expression, illumination and occlusion influencing the accuracy of recognition and it has poor performance, so the deep learning method is adopted. On the basis of face detection, a Convolutional Neural Network (CNN) based on TensorFlow, an open source deep learning framework, is proposed for face recognition. Experimental results show that the proposed method has better recognition accuracy and higher robustness in complex environment.
基于TensorFlow的卷积神经网络人脸识别
人脸识别是计算机视觉领域的一个研究热点,对特定敏感字符的检测和识别具有很高的实用价值。研究发现,在传统手工制作的特征中,存在姿势、面部表情、光照、遮挡等不受控制的环境影响识别的准确性,性能较差,因此采用深度学习方法。在人脸检测的基础上,提出了一种基于开源深度学习框架TensorFlow的卷积神经网络(CNN)用于人脸识别。实验结果表明,该方法在复杂环境下具有较好的识别精度和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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