Artificial Intelligence for Face Recognition in Security Systems: A Review of Algorithms and Challenges
El El-Sayed, Anis Ben Ghorbal
Source abstract
FRT is acknowledged as one of the successful advancements of biometric applications in security, surveillance, health care and innovative solutions. More so, the past decade has seen improvements in deep learning, pre-trained Neural Network Convolutional Neural Networks (CNNs), and combining methods such as ensembles, which have highly improved the FRT's Accuracy and efficiency. Nonetheless, several issues remain – facial expression, illumination, demographic biases or adversarial and backdoor threats. Such limitations require new approaches and tools to enhance FRT's reliability and ethical use. The current review also presents ethical concerns and the social consequences of using FRT.
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