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arXiv · 1912.02983

DeepEthnic: Multi-Label Ethnic Classification from Face Images

Katia Huri·Eli David·Nathan S. Netanyahu
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Abstract

Ethnic group classification is a well-researched problem, which has been pursued mainly during the past two decades via traditional approaches of image processing and machine learning. In this paper, we propose a method of classifying an image face into an ethnic group by applying transfer learning from a previously trained classification network for large-scale data recognition. Our proposed method yields state-of-the-art success rates of 99.02%, 99.76%, 99.2%, and 96.7%, respectively, for the four ethnic groups: African, Asian, Caucasian, and Indian.

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BibTeXRIS

Katia Huri, Eli David, Nathan S. Netanyahu. 2019-12-06. DeepEthnic: Multi-Label Ethnic Classification from Face Images. https://doi.org/10.1007/978-3-030-01424-7_59

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