Face Recognition Attendance System

Abstract

Using a Face Recognition algorithm in conjunction with Linear Discriminant Analysis, this study
aims to examine the attendance proctor. Procedures and Materials: The face recognition problem
is defined using the Face API, which compares the differences between two facial photographs.
The model for face recognition is a difference space two-class issue. You may classify facial
similarities as either those between separate people or between people of the same individual.
Using the following GPower settings: α=0.05 and power=0.80, a sample size of 10 was
calculated for each group using the GPower 3.1 program. Findings: Compared to Linear
Discriminant Analysis (92.86%), Face Recognition Algorithm (96.43%) improves item
identification. Final Thoughts: When pitted against Linear Discriminate Analysis, Face
Recognition Algorithm Comes Out on Top.