Face Recognition Based Attendance System Using Machine Learning
K R Rittymariya, Mr. Jinson Devis · Zenodo (CERN European Organization for Nuclear Research) · 2023
Abstract— The aim of this project is to develop a face recognition-based attendance system using machine learning techniques. The venture employments OpenCV and NumPy libraries to execute a profound learning show that can recognize faces and check participation in like manner. This extend employments the K-Nearest Neighbors (KNN) calculation from the scikit-learn library to prepare a show for confront acknowledgment. The KNN calculation is actualized through the KNeighborsClassifier lesson of scikit-learn. The trained KNN model is then saved as a pickle file using the joblib module. The trained model is then used to detect and recognize faces in real-time through a webcam feed. The attendance is marked automatically by comparing the detected face with a database of registered faces.