Revisor

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Revisor monitors elections, counts voters, detects violations, and aids recounts with 98% accuracy using computer vision and neural networks.

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What is Revisor?

Revisor is a neural network-based software package designed to monitor electoral procedures, count the number of actual voters, detect violations, and expedite manual recounts. It utilizes computer vision technology and trainable neural networks to recognize physical objects, track movements, and distinguish voting events at polling stations. The system can independently count voters with high precision and has reported up to 98% accuracy in detecting discrepancies in voter turnout. Revisor can be customized for different types of voting procedures and electoral systems, making it adaptable to various elections worldwide.

Who created Revisor?

Revisor was created and launched by an AI company called "Poll Watcher" in the field of neural network-based software for monitoring electoral procedures. The system was launched on April 6, 2023. Revisor uses computer vision technology to monitor electoral procedures and count the number of actual voters with high precision. It can detect violations, speed up manual recounts, and generate formal complaints, making it a versatile and reliable tool for election monitoring.

What is Revisor used for?

Detect ballot boxes on video recordings
Count the number of voters who cast their ballots
Identify polling stations with falsified turnout
Draft a formal complaint
Speed up manual recounts
Detection of multiple violation types
Trainable to work with different electoral systems
Applicable in any country
Process millions of hours of video
Customizable to different procedures

Who is Revisor for?

Journalists
Election observers
Investigative teams

How to use Revisor?

To use Revisor, follow these steps:

Understand Revisor: Revisor is a neural network-based software that monitors electoral procedures, counts actual voters, detects violations, and expedites manual recounts.
System Operation: Revisor uses trainable neural networks to recognize objects, track movements, detect voting events, and count voters with precision.
Features: It can detect and outline ballot boxes, count voters accurately, identify falsified turnout, detect violations, and facilitate the creation of formal complaints.
Detecting Violations: Revisor identifies election procedure violations by utilizing neural networks to recognize objects and voting events, detecting discrepancies between official and actual turnout.
Customization: Revisor is trainable to adapt to various voting procedures, elections, and electoral systems, making it versatile for different countries.
Reliability: It has reported up to 98% accuracy in detecting violations, depending on camera and ballot box positions in polling stations.
Data Processing: Revisor processes video data immediately after elections, allowing for timely results and retrospective analysis.
Drafting Complaints: It assists in drafting formal complaints by identifying falsified turnout through video analysis.
Cost: While the specific price is not mentioned, Revisor is highlighted as an inexpensive option compared to traditional methods.
Success Stories: Revisor has successfully processed extensive video data from elections, revealing significant discrepancies and aiding investigations.

For more detailed instructions or specific inquiries, contact Revisor at [email protected] or +370 61 33 88 61.

These steps provide a comprehensive guide to effectively using Revisor for monitoring electoral procedures and ensuring compliance.

Pros

High precision tracking
98% accuracy
Trainable neural network
Customizable to different procedures
Detects multiple violation types
Speeds up manual recounts
Applicable to video operations
Immediate and long-term results
Fast, reliable, inexpensive
Detects ballot boxes on video
Counts actual voter turnout
Identifies falsified polling stations
Drafts formal complaints
Works in any country
No scale limits

Cons

Requires video recordings
Accuracy depends on camera setup
Can't detect all violation types
Doesn't auto-resolve detected discrepancies
Possible false positives/negatives
Expensive storage for video data
Need to manually train system
Depends on quality of video
May miss subtle violations
Requires high computational power

Pros

Cons

High precision tracking
98% accuracy
Trainable neural network
Customizable to different procedures
Detects multiple violation types
Speeds up manual recounts
Applicable to video operations
Immediate and long-term results
Fast, reliable, inexpensive
Detects ballot boxes on video
Counts actual voter turnout
Identifies falsified polling stations
Drafts formal complaints
Works in any country
No scale limits

Requires video recordings
Accuracy depends on camera setup
Can't detect all violation types
Doesn't auto-resolve detected discrepancies
Possible false positives/negatives
Expensive storage for video data
Need to manually train system
Depends on quality of video
May miss subtle violations
Requires high computational power

Revisor FAQs

What is Revisor?: Revisor is a neural network-based software package that uses computer vision technology to monitor electoral procedures and count the number of actual voters.

How does Revisor work?: Revisor works using a trainable neural network that recognizes physical objects, tracks their relative movements, and distinguishes voting events from other activities at a polling station.

What can Revisor do?: Revisor can detect ballot boxes on video recordings, count the number of voters who cast their ballots, identify polling stations with falsified turnout, draft a formal complaint, and speed up manual recounts.

How does Revisor detect electoral procedure violations?: Revisor detects electoral procedure violations by utilizing neural networks to recognize physical objects and identify voting events at polling stations. It detects discrepancies between the official and actual turnout at polling stations and reports these anomalies.

Can Revisor be used in any country?: Yes, Revisor can be used in any country. The system is trainable, meaning customers can teach it to work with different types of voting procedures, elections, and electoral systems.

How reliable is Revisor in detecting electoral violations?: Revisor is highly reliable in detecting electoral violations, with reported anomalies and discrepancies detected with up to 98% accuracy.

Can Revisor detect multiple types of electoral violations?: Yes, Revisor can detect multiple types of electoral violations by recognizing physical objects, tracking their movements, and distinguishing voting events.

What are Revisor's system development stages?: The system development stages for Revisor include the Prototype stage from December 2019 to July 2020, the System Finalization stage from August 2020 to September 2021, and the current stage of Multiple voting detection module.