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Face Recognition Based Attendance System Using Machine Learning Algorithms

Face recognition refers to the process of recognising a person by their facial traits. Various computer vision methods, including face detection, expression detection, and numerous video surveillance applications, can leverage a facial characteristic. Face recognition systems have recently drawn the attention of researchers. Three alternative approaches, including SVM, MLP, and CNN, have been presented in this strategy. DNN is used to detect faces. The features are extracted using PCA and LDA feature extraction methods for SVM and MLP-based approaches. In a CNN-based technique, the photos were provided as a feature vector directly to the CNN module. The suggested method demonstrates good recognition accuracy for a CNN-based method. On a self-generated database, the SVM, MLP, and CNN correspondingly reach testing accuracy of roughly 98%. final year project is based on IEEE Paper.this will be one of the best Final year engineering project for computer science. Components that we will provide are.
1.complete documentation support
2.complete working hardware/software implemented in students environment
3.classes will held accordingly.

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