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BitRefine Video Recognition Takes CCTV to the Next Level

Use advanced neural analytics to automate your CCTV.

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Your CCTV is not just a footage. It is your Big Data.

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Control number of the objects in restricted areas (and the movements’ direction)

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The camera is constantly moving? Not a problem.

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Apply different rules to different objects. (Motorbike vs person)

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The system understands if a person stands, sits, or lies. Use this information in your scenarios.

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Let your cameras detect people in blind areas around heavy machinery.

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You will know immediately if a worker enters the area without personal protective equipment.

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Record objects’ size, colors, speed, etc. and use it as quick search criteria.

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Connect your thermal cameras detect people, vehicles, vessels at long distance.

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You can recognize faces OR obfuscate them.

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Improving fire protection system? You can rely on the advanced neural networks.

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Need to add OCR or Barcode reader to the existing recognition case: Easy!

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Need to detect people, capture license plates, recognize faces? You can have it all at once!

The platform is exceptionally flexible and lets you do whatever you need.
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Connect a microphone and the system will tell you what it hears.

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See how the next level recognition platform looks like

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Now you can work in harsh environment.

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The accuracy is our top priority.

We’re striving to ensure the most accurate results possible.
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Leverage ultimate GPU optimization

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Reduce project’s cost by running recognition on small ARM-based compute units

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Scale up your system

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To integrate or not to integrate? You choose!

Simple integration – SQL / HTTP / Serial
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Connect your favorite IP-cameras.

We support 99% of the global CCTV brands.
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BitRefine Heads is about integrating CCTV into your enterprise data management systems.

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Both commercial and government sectors are heading toward neural-based surveillance

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Cities and law enforcement

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Industrial sector

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Construction

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Mobile network operators

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Airports

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Retail

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Border security

Find out how to have all this data now

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