Published Paper Details:

The majority of the time allotted to the professors for teaching is spent recording the attendance of the pupils who are present in the class. This is viewed as a problem because it deprives teachers of time they could use for teaching and interacting with students, as well as because it causes greater disruption and a loss of decorum in the classroom. The current manual attendance management system is further complicated by the existence of proxy attendance. These issues are addressed by an automatic attendance system, which monitors students' attendance in each class using a continuous stream of images from a video streaming device placed within the classroom. The suggested remedy might lessen the time spent by teachers monitoring attendance will also lessen the commotion in the classroom. For automated face identification utilising Deep Learning models like YOLO-v3 (You Only Look Once) and face recognition using Siamese Network, this piece of study offered a superior conclusion. The model has hardware that allows it to keep track of pupils' attendance in rooms with cameras. For the purpose of storing student information, a database is kept up to date. The data in the database can be changed, destroyed, or both. The framework has a connection to a dynamic web page that facilitates obtaining the attendance record directly. There are many different institutions, colleges, and universities that can employ this sophisticated face recognition-based attendance system.