Open AccessA Survey on Performing E-Voting through Facial Recognition
Author(s) -
Pratik Hopal,
Alkesh Kothar,
Swamini Pimpale,
Pratiksha More,
J. B. Patil
Publication year - 2021
Publication title -
international journal of scientific research in science and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-602X
pISSN - 2395-6011
DOI - 10.32628/ijsrst218318
Subject(s) - voting , ballot , computer science , process (computing) , identification (biology) , biometrics , facial recognition system , artificial intelligence , machine learning , computer security , pattern recognition (psychology) , political science , botany , politics , law , biology , operating system
The election procedure is one of the most essential processes to take place in a democracy. Even though there have been immense technological advancements, the process of election has been highly limited. Most of the election procedures have been performed using ballot boxes which is an old process and needs to be updated. The security of such practices is also a concern as the identification of the voters is being done manually by the election officers. This process also needs an improvement to increase accuracy and reduce human errors by automating the process. Therefore, for this purpose, this research article analyzes the previous researches on this paradigm. This allows an effective understanding of the machine learning algorithms that are used for automatic facial recognition in the E-voting systems. This paper comes to the conclusion that the Recurrent Neural Networks are best suited for such an application for facial recognition. The future editions of this research will elaborate more on the proposed system in detail.