Facial Recognition for Remote Electronic Voting – Missing Piece of the Puzzle or Yet Another Liability?

2021 ◽  
pp. 77-93
Author(s):  
Sven Heiberg ◽  
Kristjan Krips ◽  
Jan Willemson ◽  
Priit Vinkel
Keyword(s):  
Facial Recognition ◽  
Electronic Voting

TOUCHLESS ELECTRONIC VOTING MACHINE WITH AN AI-FACIAL RECOGNITION

2021 ◽  
Author(s):  
Rajendra P Prasad ◽  
Sunil K N Kumar ◽  
Ravi Gatti ◽  
M Pranav ◽  
G. Rahul ◽  
...  
Keyword(s):  
Facial Recognition ◽  
Electronic Voting ◽  
Voting Machine

Biometric Authentication in E-Voting through RNN

2021 ◽  
pp. 434-442
Author(s):  
Alkesh Kothar ◽  
Pratik Hopal ◽  
Pratiksha More ◽  
Swamini Pimpale ◽  
Dr. J. B. Patil
Keyword(s):  
Facial Recognition ◽  
Electronic Voting ◽  
Performance Metric ◽  
Single Person ◽  
Election Process ◽  
Voting System ◽  
Security Concerns ◽  
The Right ◽  
Electronic Voting System ◽  
Democratic Country

In a democratic country the election process and the right to vote are one of the most significant aspects. This is due to the fact that in a democratic country the sole administrator and the decision maker for the entire country needs to be elected in a fair and just manner from amongst the citizens of the country. This procedure has been effectively performed manually and physically by the utilization of ballot elections. This is a highly inefficient form of election that needs to be upgraded in this day and age of information and electronic supremacy. But the considerable concerns for developing an electronic voting scheme was the security concerns regarding multiple voting performed by a single person. Therefore to introduce an effective and useful technique which also addresses the security concerns an effective methodology for electronic voting through facial recognition has been proposed in this research article. The proposed methodology utilizes the open-source open CV library along with Recurrent Neural Networks to achieve highly accurate facial recognition for a secure electronic voting system. This approach has been significantly e evaluated for their performance metric which has achieved suitable results.

Perceptual Effects and Recollective Experience in Face Recognition

2005 ◽  
Vol 52 (3) ◽  
pp. 224-231 ◽  
Author(s):  
Chrisanthi Nega
Keyword(s):  
Face Recognition ◽  
Recognition Memory ◽  
Congruency Effect ◽  
Facial Recognition ◽  
Memory Systems ◽  
Study Time ◽  
Perceptual Fluency ◽  
Recollective Experience ◽  
Trace Strength ◽  
Size Congruency

Abstract. Four experiments were conducted investigating the effect of size congruency on facial recognition memory, measured by remember, know and guess responses. Different study times were employed, that is extremely short (300 and 700 ms), short (1,000 ms), and long times (5,000 ms). With the short study time (1,000 ms) size congruency occurred in knowing. With the long study time the effect of size congruency occurred in remembering. These results support the distinctiveness/fluency account of remembering and knowing as well as the memory systems account, since the size congruency effect that occurred in knowing under conditions that facilitated perceptual fluency also occurred independently in remembering under conditions that facilitated elaborative encoding. They do not support the idea that remember and know responses reflect differences in trace strength.

Facial recognition technologies and the new physiognomic era

2020 ◽  
Vol 43 (2) ◽  
pp. 45-56
Author(s):  
Abigail Nieves Delgado
Keyword(s):  
Facial Recognition ◽  
Personal Identification ◽  
Digital Photographs ◽  
Different Types ◽  
Recognition Systems ◽  
The Way

The current overproduction of images of faces in digital photographs and videos, and the widespread use of facial recognition technologies have important effects on the way we understand ourselves and others. This is because facial recognition technologies create new circulation pathways of images that transform portraits and photographs into material for potential personal identification. In other words, different types of images of faces become available to the scrutiny of facial recognition technologies. In these new circulation pathways, images are continually shared between many different actors who use (or abuse) them for different purposes. Besides this distribution of images, the categorization practices involved in the development and use of facial recognition systems reinvigorate physiognomic assumptions and judgments (e.g., about beauty, race, dangerousness). They constitute the framework through which faces are interpreted. This paper shows that, because of this procedure, facial recognition technologies introduce new and far-reaching »facialization« processes, which reiterate old discriminatory practices.

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