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Dimensionality Reduction Using Principal Component Analysis for Lecture Attendance Management System

机译:使用讲座考勤管理系统的主要成分分析减少维数

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摘要

Face recognition based on PCA is incorporated in this attendance management system. The impact of the Viola-Jones algorithm in face detection has been highlighted in the paper. From the experimental results, it has been found that recognition accuracy of the proposed algorithm is 98.2% for the database without occlusion and 75% with occlusion for K ideal. Results also show that ideal value for RR for database 1 without occlusion is 0.267, and with occlusion, it is 0.4. Results also show that varying lighting conditions will degrade the performance of the algorithm.
机译:基于PCA的人脸识别纳入了本出席管理系统。 纸上突出了副议论算法在脸部检测中的影响。 从实验结果来看,已经发现所提出的算法的识别准确性为数据库的98.2%,而没有闭塞,75%具有K理想的闭塞。 结果还表明,没有闭塞的数据库1的RR的理想值为0.267,并且随着闭塞,它为0.4。 结果还表明,不同的照明条件会降低算法的性能。

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