Comparison of Two Face Recognition Machine Learning Models

Machine learning (ML) is one of the fastest-developing topics today, straddling boundary between statistics and computer science, as well data science. It a type artificial intelligence that allows software applications to become more accurate at predicting outcomes without being explicitly programmed. And addresses difficulty way assemble gadgets enhance themselves via experience, make conclusions with minimum human assistance. For this purpose, there arises need use various statistical methods face recognition’ models, such (DeepFace) (OpenFace). DeepFace most lightweight recognition facial attribute analysis library for Python, currently on verge human-level precision. OpenFace other hand an open source deep model based Google's Facenet model. In paper, we will discuss comparison two models calibrators (Accuracy, Error Rate Verification Time). showed higher accuracy rate by (3%) than OpenFace, lower error (3%). Whereas delivered time shorter (0.061323) second.