Zebra Deep Learning

DL-02050-01
Out Of Stock
  • Deep Learning for
    • Aurora Vision Studio
    • Aurora Vision Library
  • Works with GPU and CPU
  • Highest Performance

For pricing and delivery information, please request a quotation.

Request Quote

Description

This add-on product further enhances the already impressive outputs of AuroraTM Vision Studio and AuroraTM Vision Library software with a set of industrial-quality deep learning-based tools, including optical character recognition (OCR). In AuroraTM Deep Learning, advanced deep learning capabilities recognize the way imaging is used in more unusual vision applications – and evolve accordingly.

With use cases across multiple industry verticals, this software enables solutions for complex machine vision problems that were previously impossible to achieve with traditional algorithms and approaches. Now, for example, machines and manual operators are able to use it to find complex and irregular surface defects or accurately read blurred, poorly lit, or damaged characters printed on glossy surfaces of product packaging.

Further optimize machine vision solutions
Promote the benefits of deploying AuroraTM Deep Learning to further optimize your customers’ machine vision capabilities. This add-on software uses a set of advanced deep learning-based tools to help improve the quality and operational efficiency of existing machine vision solutions.

Evolve with real-world learning
AuroraTM Deep Learning enables industrial image analysis applications to employ a deep learning model trained using a set of real-world examples. Just 20-30 image samples can help existing machine vision solutions detect objects, defects, or features automatically, as well as identify point location and perform instance segmentation.

Comprehensive range of use cases
AuroraTM Deep Learning can be used for a wide variety of use cases. These range from identifying different parts, surface defects, and correct processes in pick and place industrial applications, for example, to rejecting poorly presented sushi boxes in retail settings and helping to identify potential bone fractures in X-ray images.

Notes:Perpetual License

User Manuals