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Adaptive Vision Studio is data-flow based software designed for machine vision engineers. It does not require any programming skills, but it is still so powerful that it can win even with solutions based on low-level programming libraries. And this has been proved with some of the most interesting vision systems in the world. What is more, the architecture is highly flexible, ensuring that users can easily adapt the product to the way they work and to specific requirements of any project. Why Adaptive Vision Studio? - Because you work much faster than with low-level programming. - Because this is the most powerful graphical software on the market. - Because you are getting everything you need for industrial image analysis - together with the highest performance and flexibility. - Because the world is changing and new challenges require new approaches. Deep Learning Add-on is a new breakthrough in machine vision applications. It is a set of ready-made tools which are trained with Good and Bad samples, and which then detect defects or features automatically. Internally it uses large neural network structures, designed and optimized by our research team for use in industrial inspection systems. For the user, however, they are provided as simple filters with very few parameters, and with easy-to-use graphical tools for convenient execution of the training process. Deep Learning Add-on truly embodies the main principles of Adaptive Vision: - Intuitive - can be used even by users with no programming skills - Powerful - unleashing advanced capabilities of neural networks - Adaptable - deep learning models can be retrained to include new features. In 2021 Adaptive Vision became part of Zebra Technologies, a NASDAQ-listed S&P 500 company.

Adaptive Vision Questions

The Adaptive Vision annual revenue was $5 million in 2026.

11 people are employed at Adaptive Vision.

Adaptive Vision is based in Gliwice, Silesian Voivodeship.

The NAICS codes for Adaptive Vision are [423, 42343, 42, 4234].

The SIC codes for Adaptive Vision are [50, 504].

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