Neonatal Face Recognition of Infants for Reduction of Swapping of Babies

Neonatal baby swapping is a grave issue surrounding the welfare and custody of a child. The proposed system aims to thwart baby swapping from hospitals or healthcare institutions by installing corrective measures at every step of the way. Our paper discusses the ordeals and distress experienced by families due to baby switching and preventive measures that leverage AI and computer vision in particular. We also discuss the privacy concerns during data collection and challenges faced during inference due to a baby's peevish tendencies, and the measures taken to overcome these pitfalls. Our paper examines earlier studies and builds upon those ideas to find the best possible outcome and a solution to prevent baby switching and alleviate any stress during a fragile period.