Enhanced Attendance Management of Face Recognition Using Machine Learning - Ravipati Sowmya.; Modem Lasya.; Yellinedi Sahith.; Namburi Tejeswara Rao.; Sk Sajida Sultana. (ITM Web of Conferences)
Conventional attendance tracking has been very timeconsuming, error-prone, and often requires a certain amount of human input and verification. Automating such solutions by using face recognition technology has thus become a viable way to deal with these problems. Our approach does not require pre-registered datasets since it automatically captures and identifies faces from a live camera stream using machine learning to automate attendance. In the alternative, real-time training takes place on location with on-location photos, thereby allowing the system to adapt to specific conditions including lighting variations, subtle facial planes, and even expressions. This results in excellent accuracy and consistency for use in all kinds of scenarios, such as offices, learning institutions, or events.