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Wireless Personal Communications
Erschienen in: Wireless Personal Communications 4/2021

16.02.2021

Performance Evaluation of Machine Learning Based Face Recognition Techniques

verfasst von: Sahil Sharma, Vijay Kumar

Erschienen in: Wireless Personal Communications | Ausgabe 4/2021

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Abstract

The robustness of machine-learning model-based face recognition techniques to image processing attacks using the quantization of extracted features is presented. Recently developed face recognition techniques based on machine learning models have been outperformed over traditional face recognition techniques. An efficient face recognition technology should be able to resist various image processing attacks. This paper presents the simulation results by evaluating ten variants of machine-learning-based face recognition techniques on ten well-known image processing attacks. The quality of face recognition techniques has been assessed on recognition accuracy. The performance has been evaluated on two well-known face databases viz. Bosphorus and University of Milano Bicocca (UMB) face database. The experimental results reveal that the Subspace discriminant ensemble-based face recognition model has consistently performed in most image processing attacks. All image processing attacks have been visually verified and presented.
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Metadaten
Titel
Performance Evaluation of Machine Learning Based Face Recognition Techniques
verfasst von
Sahil Sharma
Vijay Kumar
Publikationsdatum
16.02.2021
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 4/2021
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-021-08186-9

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