REVISOR is a software solution powered by neural networks, employing computer vision to oversee elections and tally the actual number of voters.
This software offers a cost-effective alternative to traditional methods for election observation missions. The Revisor system accurately monitors physical objects, identifies voting events, and distinguishes them from other polling station activities (achieving up to 98% accuracy).
Furthermore, it's a trainable neural network, enabling users to adapt it to different voting procedures, elections, and electoral systems worldwide.
The system can identify various types of irregularities and expedite manual recounts. This software is suitable for video-based operations, delivering results immediately after an election or even months/years later.
Revisor is a swift, dependable, and economical system designed to identify ballot boxes in video footage, count voters, pinpoint polling stations with manipulated turnout figures, generate formal complaints, and accelerate manual recounts.
Success stories demonstrate Revisor's effectiveness in detecting discrepancies between official and actual voter turnout at polling stations, alerting users who can then address the underlying issues.
In summary, Revisor is an AI tool that effectively utilizes neural networks to monitor elections and ensure compliance with electoral processes.
High-precision tracking capabilities
Operates with 98% accuracy
Features a trainable neural network
Requires video footage for operation
Accuracy is dependent on camera positioning
Cannot detect all forms of violations

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