A Deep Neural Network for face Recognition
K. Sai Krishna1, G. Sreenivasa Raju2, P. Praveen Kumar3
1K. Sai Krishna, Assistant Professor, Department of Electronics and Communication Engineering, Anurag Group of Institutions Ghatkesar, Medchal Hyderabad (Telangana), India.
2G. Sreenivasa Raju, Assistant Professor, Department of Electronics and Communication Engineering, Anurag Group of Institutions Ghatkesar,Medchal Hyderabad (Telangana), India.
3P. Praveen Kumar, Assistant Professor, Department of Electronics and Communication Engineering, Anurag Group of Institutions Ghatkesar, Medchal Hyderabad (Telangana), India.
Manuscript received on 07 October 2019 | Revised Manuscript received on 21 October 2019 | Manuscript Published on 26 December 2019 | PP: 420-423 | Volume-8 Issue-12S October 2019 | Retrieval Number: L110510812S19/2019©BEIESP | DOI: 10.35940/ijitee.L1105.10812S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Face recognition is used to biometric authentication method to analyze the face extract and photographs useful to reputation formation from them, which can be usually called as a characteristic vector this is used to differentiate the organic features. In this paper to detect the suspect by extracting facial features from the captured image of the suspect from CCTV and match it with the pictures stored in the database and also to achieve an accuracy rate of 100 %, negligible loss using deep learning technique. For extracting the facial features, we are using deep learning model known as Convolutional Neural Network (CNN). It is one of the best models to extract features with the highest accuracy rate.
Keywords: Face Recognition, Convolutional Neural Network, Principal Component Analysis, Support Vector Machine.
Scope of the Article: Pattern Recognition