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Fast and accurate user identification and verification is always desirable. Face recognition, which is machine recognition of a person's face by analyzing patterns on facial features, is becoming important for security and validation. Less interaction from users contributes high enrolment as well as easily applicable for current technology further adds its importance. In this regard, we propose a Multi-tasked Convolutional Neural Network (CNN) based face recognition technique previously done with eigenfaces but CNN has better accuracy. This project proposes to use this technology for identifying criminals who are on the run from their previous records. An NCRB (National Crime Records Bureau) report shows that 70% of crimes are repeatedly committed by the same criminals. These criminals can be identified by the face recognition from an image or video frame which is captured by the cameras which are installed in various locations and it can also be used for identifying missing children. This system will decrease crimes and ensure security in our society.
- et al. (Fri,) studied this question.