Virtual ATM through Fingerprint and Face recognition using Deep Learning
Author(s):
Vaishnavi M. Shinde, Dhanashri B. Shinde, Pravin B. Shinde, Aditya V. Wandhekar, Pallavi S. Kohakade
Keywords:
Virtual ATM, Biometric recognition. Face recognition, Fingerprint Recognition, Channel Boosted Convolutional Neural Networks.
Abstract
AbstractFingerprints and facial features of the individual are being used in biometric authentication techniques, which are increasingly extensively used across significant implementations. Despite the fact that there multiple facial recognition systems accessible. A greater number of research should unearth factors that improve efficiency and accuracy. Facial as well as fingerprint identification play an important part in the identifying process since they do not need human assistance, unlike some other biometrics methods. This not only proves the huge potential to create far greater protection for such Virtual ATM transactions, but also explains the reasoning why biometric identification systems have been attracting so much attention. Therefore, for this purpose an effective framework for biometric authentication on Virtual ATMs through the use of biometric features, such as Facial and Fingerprint have been proposed. The presented framework utilizes Live Streaming and Region of Interest along with Channel boosted Convolutional Neural Networks and OTP authentication has been implemented. The framework has been measured using lengthy experimentations to achieve quite reassuring outcomes.
Article Details
Unique Paper ID: 158680

Publication Volume & Issue: Volume 9, Issue 10

Page(s): 381 - 387
Article Preview & Download


Share This Article

Join our RMS



Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Latest Publication

Call For Paper

Volume 11 Issue 1

Last Date for paper submitting for Latest Issue is 25 June 2024

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies

Important Links

Browse Rsearch papers