000			01716nam a22001457a 4500
008			210806b ||||| |||| 00| 0 eng d
100			_aADEMUWAGUN, Oluwaseyifunmi Temitope _98697
245			_aAn Online Attendance System Using Computer Vision with Face Detection and Recognition
250			_aDr. OKUNOYE, B. O.
260			_aIbafo _bComputer Science and Mathematics _c2020
300			_ax,; 50p. _bdia, tables
520			_aOver the last ten years, face recognition has become a common field in computer vision science and one of the most promising image processing and comprehension applications. This project is based on the implementation of computer vision for an Electronic Attendance System using automatic face recognition technologies as a form of biometrics. Face recognition based attendance system is a process of identifying the students face for taking attendance. The aim of this project is to create an efficient and reliable facial recognition software that would be able to detect a person with high accuracy. A large amount of algorithms and techniques have been developed for improving the performance of face recognition but the concept to be implemented here is Deep Learning. It helps to transform the frames of the video into images so that the attendance database can remember the identity of the student. This project was built using OpenCV (open computer vision) and Python with other frontend and backend technologies using Pycharm 2019 as the Integrated Development Environment. The E-attendance system created is useful in helping the school, lecturers and students to keep accurate records of the attendance properly.
650			_aComputer Science _91105
942			_cTHS
999			_c6161 _d6161