Integrated Multiple Neural Networks for Face Recognition in Smart Attendance System
In this modern world, technology is speeding up and plays an important role in every human beings life. Technology is meant to make a man’s life easy. It can be noticed that the schools and colleges have the ritual of taking attendance. Manually marking attendance is a time consuming process. Manual marking of attendance increase the usage of paper, which leads to the cutting of trees and global depletion. Many technical solutions have been brought into circulation but they are highly complex. Nowadays smart technologies are applied in the real world problems, so as to increase the work efficiency and save time. In this paper, a novel algorithm incorporating Multiple Radial Basis Function Neural Networks (MRBFNN) is introduced. The results obtained from various neural networks are integrated to obtain the final output. In this work, python programming is used along with OpenCV for the implementation and analysis. This algorithm paves a way to implement smart attendance system based on face recognition. Compared to existing methods, this method is efficient and less time consuming.
Keywords: Facial Recognition, Smart Attendance, Neural Network, MRBFNN, OpenCV.