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Title |
Deep Neural Networks for Face Recognition and Feature Extraction from Multi-lateral Images |
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Author |
Venkata Srinivasu Veesam, Suban Ravichandran, and Gatram Rama Mohan Babu, |
| Citation |
Vol. 22 No. 4 pp. 700-704 |
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Abstract |
Face recognition has been a strong secure system which doesn’t requires any keys or cards. To protect law enforcement, safekeeping of home, to expose phone, even to find missing persons and in many more applications face recognition has been a popular method. The practice of ascertaining operators that appeal right to use to a system, network, or device is called Authentication. Cybercriminals uninterruptedly advance their outbreaks. Security teams are facing plenty of authentication-related challenges. In addition, government interest in face recognition technologies has increased because of their high-security level and accessibility. This made the firms to focus on more intellectual instance response tactics. Facial acknowledgment technologies are quickly becoming integral parts of user security, allowing for a secondary level of user authentication. To maintain the skill to afford protected right to use without a fall in speed there is a requisite for authentication methods. We already had inspiring domino effects by boosting traditional username and password security with facial biometrics, on the other hand, swotting these techniques is obligatory to conclude how effective these methods are within different constraints. A2 stage human recognition structure embroils face identification in general. Strategy and development of a face recognition system through deep learning using Open-CV in python is proposed with this paper. Performance of face detection and recognition is affected and damaged because occlusion often leads to missed detection. The proposed work is of an optical consideration tool supervision model to shrink the recognition exactitude initiated by facial occlusion and augment the precision of face detection. The uniqueness and endorsement of the proposed work takes the method to be more strategic over other algorithms. We need speed and accuracy to identify. |
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Keywords |
facial recognition, face detection, feature extraction, convolutional neural networks, deep neural networks |
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