Face Recognition System for Medical Information Modeling Using Machine Learning

Background

When a person is identified based on their behavioural or physiological traits, biometrics is the technique of choice at the moment. Since the beginning of the twenty-first century, the physical and individual interface has played an important part in essential daily activities. However, we have been reluctant to continue this trend in the present day. A programmed society is more frequent than a private society, with mechanical representations, unsigned clients, and electronic sources of internet-related information being more common than their private counterparts. Face recognition has been related to mobile recognition systems because of the large range of visible benefits it has over traditional diagnostic techniques, which have been shown. The technology of face recognition has received a great deal of interest lately, particularly in the United States. It is utilized to draw attention to a person's individuality. As a result, facial recognition technology has depended on the human face for its accuracy. It is unknown to the general public that this facial recognition technology is capable of acting as an instantaneous fingerprint scanner. Unlike other biometric technologies like as iris recognition and central belief, facial recognition obtains images after entering a specified area on the subjects' faces. It is difficult to use computer recognition in facial recognition since the outer layer of a human face does not change much(Akbar et al., 2019).