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Deep Learning thrives when inspection isn’t clear cut

Deep learning technology might seem cutting edge, but it’s a perfect complement to machine vision inspection applications now. In this quick video overview and downloadable eBook we’ll explain the differences between the two inspection approaches and when it makes sense to use deep learning or traditional machine vision for your factory automation strategy.

This eBook cover these topics:

  1. How deep learning differs from machine vision
  2. How deep learning systems learn via neural networks
  3. Which types of applications are best suited to deep learning methods
  4. How deep learning benefits industrial manufacturing
Powered by Epson Robots, IntelliFlex software and Vision Guide, the IntelliFlex Parts Feeding System delivers a powerful solution to accommodate a wide variety of parts. 
 
Epson Vision Guide identifies part sizes, shapes and positions to automatically optimize picking order. The Flexible Feeders are compatible with a wide range of parts from 3 up to 150mm in size. Smart auto-tuning and the ability to store up to 16 part profiles allow for simple setup and quick part changeovers.
 
Seamlessly integrated with the vision system, flexible feeder and Epson RC+ software, an Epson 6-Axis or SCARA robot efficiently picks the singulated parts.
Gibson Engineering will be exhibiting at SLAS2022 in Boston.

With a fresh program highlighting life sciences discovery and research and innovations in laboratory technology, SLAS2022 will feature:

  • Immersive pre-conference Short Courses
  • Thought-provoking keynote speakers
  • An exhibition featuring laboratory automation solutions
  • Exhibitor tutorials

Visit our interactive displays featuring
laboratory automation solutions at Booth# 2444
Online Training Courses
Join us for our online training courses in Robotics, Vision, Controls, Visualization, and Safety.
Cognex In-Sight ViDi Standard
Training

February 1-2, 2022
Machine Safety Technology
& Safe Controls

February 3, 2022
Mitsubishi GX-Works3
Programming Class

February 15-18, 2022