Real-Time Face Detection on Security Surveillance Footage

Recent years have witnessed notable progressions in facial recognition technology which have been led by the inception of deep learning models-primarily Siamese Neural Networks. This article delves into the use of Siamese Neural Networks for one-shot face classification tasks, giving priority to extracting discriminative features and training deep learning models. Among the pillars of our methodology are: data collection; preprocessing; model building and real-time verification using deep learning abilities, especially Convolutional Neural Networks (CNNs). We hope that through this approach we can significantly improve the accuracy of facial recognition in real-time surveillance applications with what CNNs have to offer.