Identifying Ethnics of People through Face Recognition: A Deep CNN Approach

Joint Authors

AlBdairi, Ahmed Jawad A.
Xiao, Zhu
Alghaili, Mohammed

Source

Scientific Programming

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-07-14

Country of Publication

Egypt

No. of Pages

7

Main Subjects

Mathematics

Abstract EN

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%.

American Psychological Association (APA)

AlBdairi, Ahmed Jawad A.& Xiao, Zhu& Alghaili, Mohammed. 2020. Identifying Ethnics of People through Face Recognition: A Deep CNN Approach. Scientific Programming،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1209062

Modern Language Association (MLA)

AlBdairi, Ahmed Jawad A.…[et al.]. Identifying Ethnics of People through Face Recognition: A Deep CNN Approach. Scientific Programming No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1209062

American Medical Association (AMA)

AlBdairi, Ahmed Jawad A.& Xiao, Zhu& Alghaili, Mohammed. Identifying Ethnics of People through Face Recognition: A Deep CNN Approach. Scientific Programming. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1209062

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1209062