Marking Attendance using Modern Face Recognition (FR): Deep Learning using the OpenCV Method
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. A 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.
Author/Authors Full Name: Mohammad Gouse Galety; Firas Hussam Al Mukthar; Rebaz Jamal Maaroof; Fanar Rofoo; S. Arun
Journal Name: IEEE Xplore
Date of Publication: 01 June 2022