Face Recognition Model Using Back Propagation

  • Authors

    • R Aswini Priyanka
    • C Ashwitha
    • R Arun Chakravarthi
    • R Prakash
    2018-09-01
    https://doi.org/10.14419/ijet.v7i3.34.18973
  • Face Recognition, Deep learning, Convolutional Neural Network (CNN), Back Propagation Neural Network (BPNN).
  • Abstract

    In scientific world, Face recognition becomes an important research topic. The face identification system is an application capable of verifying a human face from a live videos or digital images. One of the best methods is to compare the particular facial attributes of a person with the images and its database. It is widely used in biometrics and security systems. Back in old days, face identification was a challenging concept. Because of the variations in viewpoint and facial expression, the deep learning neural network came into the technology stack it’s been very easy to detect and recognize the faces. The efficiency has increased dramatically. In this paper, ORL database is about the ten images of forty people helps to evaluate our methodology. We use the concept of Back Propagation Neural Network (BPNN) in deep learning model is to recognize the faces and increase the efficiency of the model compared to previously existing face recognition models.

     

     

     

  • References

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  • How to Cite

    Aswini Priyanka, R., Ashwitha, C., Arun Chakravarthi, R., & Prakash, R. (2018). Face Recognition Model Using Back Propagation. International Journal of Engineering & Technology, 7(3.34), 237-240. https://doi.org/10.14419/ijet.v7i3.34.18973

    Received date: 2018-09-04

    Accepted date: 2018-09-04

    Published date: 2018-09-01