Face Recognition with Smart Security System
Manik Rakhra, Dalwinder Singh, Arun Singh, Kamal Deep, Deepa Gupta
Abstract
Internet-based innovation has advanced significantly during the past decade. As a result, advances in security technology have become a crucial resource for protecting our daily lives. In this research, we suggest a framework for secure face recognition (SoF). In particular, we tailor this infrastructure to allowing verified customers entry into a private residence. In order to get the classifier ready, another flexible learning technique is used. For starters, we get our preliminary data from social groups and institutions. As the client continues to make use of the framework, the classifier's accuracy increases. The classifier model has been improved by employing an epic technique that makes use of human interaction and online community. Using the powerful learning framework TensorFlow, the system may be easily repurposed to work with a wide variety of devices and applications.