Marking Attendance using Modern Face Recognition (FR): Deep Learning using the OpenCV Method
Mohammad Gouse Galety, Firas Husham Almukhtar, Rebaz Jamal Maaroof, Fanar Fareed Hanna Rofoo, S. Arun · 2022 8th International Conference on Smart Structures and Systems (ICSSS) · 2022
Face Recognition and Detection encompasses an ocean of study and development involving picture analysis and algorithm-based comprehension, sometimes known as computer vision. Attendance is a right that no one can reject, and to support this right, many efforts and studies are being conducted around the world. A Deep Convolutional Neural Network (CNN) using the OpenCV model has been suggested for marking Attendance in this work. Convolutional Neural Network is employed to gain the unique features of the faces based on the distance. A wide variety of parameters influence the training of a Convolutional Neural Network (CNN) based classifier. These aspects include assembling an appropriate dataset, choosing a suitable Convolutional Neural Network (CNN), processing the dataset, and choosing training parameters to get the required classification results. The current publication compiles state-of-the-art research that used dataset preparation and artificial augmentation before training. Accuracy rates are achieved using the proposed model.