Exploring the application of neural networks for facial image reconstruction in recognition systems

Identifying a person in a digital image using computer vision is a crucial aspect of this field. The presence of external objects, such as medical masks that cover part of the face, can drastically reduce recognition accuracy and increase errors from 5% to 50%, depending on the algorithm. This paper investigates the use of neural networks, in particular the generative adversarial network (GAN), to solve the problem of reconstructing an image of a face covered by a medical mask to improve face recognition accuracy.