Real Time Gender and Age Prediction using Deep Learning Techniques
P. Tamije Selvy1, M. Sujith2, V. Sanjay3, G. Sreeram4, M. Anitha5
1Dr.P.Tamije Selvy*, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, India.
2M.Sujith, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, India.
3V.Sanjay, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, India.
4G.Sreeram, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, India.
5M.Anitha, Full-Time Ph. D Scholar, in Sri Krishna College of Technology in the Department of Computer Science and Engineering.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 30, 2020. | Manuscript published on April 10, 2020. | PP: 630-632 | Volume-9 Issue-6, April 2020. | Retrieval Number: E2906039520/2020©BEIESP | DOI: 10.35940/ijitee.E2906.049620
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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 plays a vital role in security purpose. In recent years, the researchers have focused on the pose illumination, face recognition, etc,. The traditional methods of face recognition focus on Open CV’s fisher faces which results in analyzing the face expressions and attributes. Deep learning method used in this proposed system is Convolutional Neural Network (CNN). Proposed work includes the following modules: [1] Face Detection [2] Gender Recognition [3] Age Prediction. Thus the results obtained from this work prove that real time age and gender detection using CNN provides better accuracy results compared to other existing approaches.
Keywords: Convolutional Neural Network (CNN), Face Recognition, Feature Extraction, Open CV’s Fisher Faces.
Scope of the Article: Network Architectures