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Deep Neural Architectures for Ethnicity Classification in Face Images

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dc.contributor.author Jayasekara, Buddhi G.
dc.contributor.author Hevapathige, Asela
dc.date.accessioned 2022-10-31T08:51:13Z
dc.date.available 2022-10-31T08:51:13Z
dc.date.issued 2022
dc.identifier.citation Jayasekara Buddhi G.; Hevapathige Asela (2022), Deep Neural Architectures for Ethnicity Classification in Face Images, International Research Conference on Smart Computing and Systems Engineering (SCSE 2022), Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka. 114-121. en_US
dc.identifier.uri http://repository.kln.ac.lk/handle/123456789/25412
dc.description.abstract Ethnicity is a key metric of an individual’s identity, social cluster, physical behaviour and cultural association. Accurate ethnicity identification of humans is required in numerous fields like security, legislation, social analysis and psychology. Ethnicity classification using machine learning is a complex, non-trivial and multi-dimensional research problem due to the feature complexity, class imbalance and the absence of rich data sets. In this research study, we have trained and compared four state-of-the-art deep neural models and their ensemble architectures on the problem of ethnicity classification in large-scale image data. The empirical results demonstrate that these end-to-end deep learning models and their ensemble architectures perform well in learning complex ethnic features in facial images and classifying them. From the evaluated models, Ensemble Convolutional Neural network provided the highest classification performance with 78.9% accuracy. Also, we have tested six prominent pre-trained models using transfer learning for ethnicity classification while being able to achieve comparable results. en_US
dc.publisher Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka en_US
dc.subject deep learning, ethnicity classification, image processing, neural networks, transfer learning en_US
dc.title Deep Neural Architectures for Ethnicity Classification in Face Images en_US


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