Biometric recognition model using deep convolutional neural networks and computer vision (#492)
Read ArticleDate of Conference
July 19-21, 2023
Published In
"Leadership in Education and Innovation in Engineering in the Framework of Global Transformations: Integration and Alliances for Integral Development"
Location of Conference
Buenos Aires
Authors
Ovalle, Christian
Sumire Qquenta, Daniel
Vilca Sucapuca, Julian Nestor
Sumire Qquenta, Rebeca
Abstract
Authentication of the person by means of unique features such as finger veins is used in various fields such as security. In this research, a verification method based on convolutional neural networks with the help of computer vision is proposed. Through experimentation, it was possible to create an artificial intelligence model that shows the measurements of loss and precision when verifying the images of a data set. Finally, it is concluded that the loss of biometric recognition, the lower the percentage, the better the model performs. For the modified VGG16 model, 40 epochs were carried out for training, while the Mobilenet was 50 epochs. Additionally, at the end of the execution, the proposed architecture finished in 13 minutes and 45 minutes.