Enhancing Security by Identifying Facial Check-in using Deep Convolutional Neural Network
Pulkit Singh, Ram Krishn Mishra, Siddhaling Urolagin, Vishnu Sharma · 2021 3rd International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) · 2021
Facial recognition is widely being used in many applications. In this research face recognition-based facial identification systems have been implemented to identify the person’s identity whether he/she is an insider or outsider. The system will act as a tool for strengthening the safety of any organization and can also monitor in/out attendance. The proposed system aims to also prevent imperfections of manually taking attendance and allows better accuracy. Solving the problems that arose in the regulation of the old system. A combined OpenCV and deep convolutional neural networks techniques have been used to build the model. The purpose of this research is to create a face database of known people that will help to identify individuals. The developed model validated with known images and resulted accuracy is 90% and for unknown around 60%. The time of facial recognition is also recorded as a person’s time of entry and date for validation and verification.