Efficient Profile Matching Methods Using Convolution Neural Networks

  • Dr. S. Siamala Devi, Thiraimathi S, Sriabirami R,Sinega V,

Abstract

Background: Biometrics are physical or behavioral human characteristics to that can be used to digitally identify a person to grant access to systems, devices or data. Face recognition can be a concept of biometric for safety approach. A profile describes a collection of properties, e.g. a group of abilities a person may additionally have, or a collection of talents a cricketer can also have with regard to a particular group strategy. Findings: The methodologies like Cascade Classifier and Convolution Neural Network are applied to detect face of a private. A comparison has been made among the above-mentioned methodologies and  therefore the inferred result shows that Convolution Neural Network has produced a far better performance. Therefore, CNN helps the input image to be matched with the profile in an efficient way.

Published
2020-06-04
How to Cite
Dr. S. Siamala Devi, Thiraimathi S, Sriabirami R,Sinega V,. (2020). Efficient Profile Matching Methods Using Convolution Neural Networks. International Journal of Advanced Science and Technology, 29(9s), 7186-7191. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/24426