Real time user access control on Social Network using Deep Learning

Authors

  • Mr. Siddhesh Dixit SVPCET, Nagpur, India
  • Mr. Dipak Wajgi SVPCET, Nagpur, India
  • Dr. Sunil Wanjari SVPCET, Nagpur, India.

Keywords:

CNN, LSTM, Real time user access, deep learning

Abstract

In the past few years, there has been a huge growth in the use of Social Networking Platform. Real-time age estimation has been essential in the field of human computer interaction and computer vision. Accuracy of age estimation of the face image is really challenging. In this project, we build a model which restrict user to login the social networking sites. We used Deep Learning for face recognition. After recognizing the face it will classify as per the age group. If certain age group has permission then that person will get access. We used CNN with LSTM for having more accurate prediction of biological age of the person. We used MTCNN for face detection and feature extraction.

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Published

30-06-2022

How to Cite

Mr. Siddhesh Dixit, Mr. Dipak Wajgi, & Dr. Sunil Wanjari. (2022). Real time user access control on Social Network using Deep Learning. International Journal for Research Publication and Seminar, 13(2), 246–251. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/598

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Section

Original Research Article