Yüz tanıma sistemi için VGG tabanlı özellik çıkarma

•Facial recognition technologies are one of the main aspects of many things for example; security, biometrics, and social media. That is where we go ahead to present a feature extraction for our face recognition system based on the VGG approach. We assemble a collection of facial images and then process them to keep all the images consistent and properly set to avoid poor-quality images. The prioritized model exemplifies the use of VGG16, employed to extract high-level features from faces, that follow identification by the classification algorithm. System efficiency is evaluated concerning indicators of quality, for instance, accuracy precision, recall, and F1-Score. The results show that our model, based on feature extraction using VGG, has high accuracy and an accuracy rate with an LR model is 91%, ANN 0.87, SVM 0.89, KNN 0.74, DT0,39, GB0.75, and RF 0.74for FR. The results show that our proposed works well and is efficient in facial recognition functions. We believe that this kind of research takes facial recognition technology to a new level of development and will be a great example for other studies.