Lessons from Vision 2016
22 November 2016
Greg Blackman sums up some of the main talking points at the recent Vision trade fair in Stuttgart, Germany
Matthew Dale explores vision solutions for code reading and inspection in pharmaceutical production
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MVTec’s Halcon software library includes a deep learning OCR tool with pre-trained fonts from a wide range of industries. Credit: MVTec
Engineers at KYB in front of a pick-and-place solution for handling steel metal cylinders. Credit: Pickit
Car manufacturing has been hit hard by Covid-19, but the need for automation on production lines has not diminished, as Greg Blackman finds out
A point cloud of a National Research Council Canada artefact superimposed on a CAD model. Credit: NIST
How do you choose a 3D vision system for a robot cell? Geraldine Cheok and Kamel Saidi at the National Institute of Standards and Technology in the USA discuss an initiative to define standards for industrial 3D imaging
SWIR imaging can show bruising in fruit that wouldn't be evident with a visible camera. Credit: Sony
Edmund Optics’s Thomas Armspach-Young and Boris Lange consider the optics needed to get the best out of Sony's new short-wave infrared image sensors
What kind of economic development do you expect during and after this crisis?
Findings from a two-part survey, conducted by the European Machine Vision Association, on the effects the Covid-19 pandemic could have on the machine vision industry
Credit: Drag&bot
Christoph Hellmann Santos, of the ROS Industrial Consortium Europe and Fraunhofer IPA, explains why more industrial users are now building robots through the open source software platform, Robot Operating System
