Abstract:
This project is based on the Design and Implementation of an Automated Attendance Management System. The purpose of the proposed project is to rid the attendance management system of the manual process therefore instilling reliability and efficiency to the system with the use of Face Recognition algorithms, techniques and other programming techniques to build a software for this system. The use of FaceNet as face detection algorithm and SVM classifier was critical to the functioning of the system. In this project and previously done projects many face detection methods have been used such as Haar-cascade, Histogram of Oriented Gradients, CNN and so on.
MTCNN is one of the most accurate face detection methods used with FaceNet Keras method provides better results in computation and detection of faces. It detects faces across multiple variations and scales.
This project work was built using Django framework which is a python-based framework for the quick deployment of web applications. The use of python libraries such as TensorFlow, Sci-Kit learn, Keras and others made it possible for the system to run more efficiently and accurately as these libraries were built majorly for machine learning purposes.
The Automated Attendance Management System is a far more efficient and quicker way of taking attendances a in classroom.
