Human Recognition Model Using CNN

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Published Nov 26, 2022
https://doi.org/10.47164/ijngc.v13i5.861
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Volume 13, Special Issue 5, November 2022

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Mridula Korde
Shri Ramdeobaba College of Engineering and Management, Nagpur
Abhishek Joshi
Shri Ramdeobaba College of Engineering and Management, Nagpur-13
Aditya Shrivastava
Shri Ramdeobaba College of Engineering and Management, Nagpur-13

Abstract

Since the ever increasing demand of social platforms and social media, it is highly recommended to check age and gender of the person using social websites to avoid any age restricted content. Automatic age and gender classification offers variety of applications majorly authentication, visual surveillance, customer care, biometrics. A convolutional neural network (CNN) is emerging tool for image processing and human identification. In this paper, deep- convolutional neural networks (CNN) is proposed to learn structures of human’s face and hence improve performance for recognition of human’s gender and age significantly. Here, we propose a less complex convolutional neural network design which can be effectively used in case of a small amount of learning data too. The attempts include lowering the number of parameters, boosting the network's depth, and adjusting the dropout rate to have better matching with current state-of-the-art methods using the Adience benchmark.

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Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Author Biographies

Mridula Korde, Shri Ramdeobaba College of Engineering and Management, Nagpur

Mridula Korde works as Associate Professor in Department of Electronics and Communication Engineering at Shri Ramdeobaba College of Engineering and Management, Nagpur, India. She has received her Doctorate Degree from Visvesaraya National Institute of Technology, Nagpur. She has passion of teaching with 18+ years of teaching experience in the domain of Electronics/Electronics and Communication Engineering. Her research area includes channel modeling, synchronization in wireless networks,neural networks.

Abhishek Joshi, Shri Ramdeobaba College of Engineering and Management, Nagpur-13

Abhishek Joshi is Final Year student of Department of Electronics and Communication Engineering at Shri Ramdeobaba College of Engineering and Management, Nagpur, India.

Aditya Shrivastava, Shri Ramdeobaba College of Engineering and Management, Nagpur-13

Aditya Shrivastava is Final Year student of Department of Electronics and Communication Engineering at Shri Ramdeobaba College of Engineering and Management, Nagpur, India

How to Cite
Mridula Korde, Abhishek Joshi, & Aditya Shrivastava. (2022). Human Recognition Model Using CNN . International Journal of Next-Generation Computing, 13(5). https://doi.org/10.47164/ijngc.v13i5.861
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