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Identifying Ethnics of People through Face Recognition: A Deep CNN Approach
Scientific Programming ( IF 1.672 ) Pub Date : 2020-07-14 , DOI: 10.1155/2020/6385281
Ahmed Jawad A. AlBdairi 1, 2 , Zhu Xiao 1 , Mohammed Alghaili 1
Affiliation  

The interest in face recognition studies has grown rapidly in the last decade. One of the most important problems in face recognition is the identification of ethnics of people. In this study, a new deep learning convolutional neural network is designed to create a new model that can recognize the ethnics of people through their facial features. The new dataset for ethnics of people consists of 3141 images collected from three different nationalities. To the best of our knowledge, this is the first image dataset collected for the ethnics of people and that dataset will be available for the research community. The new model was compared with two state-of-the-art models, VGG and Inception V3, and the validation accuracy was calculated for each convolutional neural network. The generated models have been tested through several images of people, and the results show that the best performance was achieved by our model with a verification accuracy of 96.9%.

中文翻译:

通过人脸识别识别人的种族:深度 CNN 方法

在过去十年中,人们对人脸识别研究的兴趣迅速增长。人脸识别中最重要的问题之一是人的种族识别。在这项研究中,一个新的深度学习卷积神经网络旨在创建一个新模型,该模型可以通过面部特征识别人的种族。新的民族数据数据集包含从三个不同民族收集的 3141 张图像。据我们所知,这是为人类种族收集的第一个图像数据集,该数据集将提供给研究社区。新模型与两个最先进的模型 VGG 和 Inception V3 进行了比较,并计算了每个卷积神经网络的验证精度。生成的模型已经通过多张人物图像进行了测试,
更新日期:2020-07-14
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