Journal
ACM COMPUTING SURVEYS
Volume 48, Issue 1, Pages -Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/2791121
Keywords
Algorithms; Security; Performance; Face recognition; bio-inspired computing; feature selection; optimization; evolutionary algorithms; artificial neural networks; swarm intelligence
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Funding
- Ministry of Education, Malaysia
- Universiti Sains Malaysia
- ERGS [203/PKOMP/6730075]
- RUI [1001/PKOMP/811290]
- [304/PKOMP/6312153]
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An increased number of bio-inspired face recognition systems have emerged in recent decades owing to their intelligent problem-solving ability, flexibility, scalability, and adaptive nature. Hence, this survey aims to present a detailed overview of bio-inspired approaches pertaining to the advancement of face recognition. Based on a well-classified taxonomy, relevant bio-inspired techniques and their merits and demerits in countering potential problems vital to face recognition are analyzed. A synthesis of various approaches in terms of key governing principles and their associated performance analysis are systematically portrayed. Finally, some intuitive future directions are suggested on how bio-inspired approaches can contribute to the advancement of face biometrics in the years to come.
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