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DEEP LEARNING

Making the Impossible, Possible. 
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How it Works

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​​Trace

Trace features on a few images. Even use tracings you already have.

Train

A deep neural network learns how to recognize what you've traced.
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Apply

Run your model on a new image to detect complex features.
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Examples

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Detecting grains while ignoring twins has challenged the community for decades.
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Model trained on 25 images in 40 minutes on a GPU.
Applied to new image in 2 seconds.

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Conventional methods struggle with low contrast and noise in these complex features.

Model trained on 16 images in 60 minutes on a GPU.
Applied to new image in 3 seconds.

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14 Day Free Trial
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Detecting these cells was impossible for traditional approaches, and even some humans.

Model trained on 600 images in 20 hours on a GPU.
Applied to new image in 2 seconds.

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Complex, overlapping nanofiber networks have little contrast with the background.

Model trained on 36 images in 40 minutes on a GPU.
Applied to new image in 1.5 seconds.

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Documentation

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  • About
  • Applications
    • Materials Science
    • Life Science
    • Drone & Survey
    • Recipe Templates
    • Integrations >
      • MIPAR Live
      • Python API
      • REST API
      • Granta MI
    • Webinars
    • Articles & Citations
  • Deep Learning
  • Purchase
    • Request a Quote
    • Find a Distributor
    • Student Store
  • User Resources
    • Udemy Course
    • Help desk
    • Forum
    • Tutorials
    • FAQ
    • User Manual
  • Download Trial