Accuracy Improvement in the Attendance Marking System using Human Face Recognition with Inception Algorithm and Comparing with Light Gradient Boosting Machine (LGBM) Algorithm

This research is about the human face recognition for attendance marking system using Inception algorithm compared with LGBM algorithm with respective accuracy. For this analysis 38 samples were taken in two groups with 19 samples each. Group 1 uses Inception algorithm and group 2 uses LGBM algorithm. By this research, the dataset is imported and then Inception code is implemented with the help of Google Collab software. The sample size is calculated from the values which are obtained from previous studies with the help of online statistical analysis tools with the pretest power 80% and the alpha value of 0.05. From simulation results, Inception algorithm accuracy is 88% and LGBM algorithm accuracy is 97% with a significance of 0.020 which is less than 0.05 (p<0.05). For the given dataset LGBM algorithm gives better accuracy than Inception algorithm in terms of Prediction for the face recognition.