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You searched for "deep learning"

14 results:

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Deep Learning
Deep Learning
Artificial intelligence for SICK sensors
  • Interference takes place directly on programmable SICK products
  • Training of neuronal networks in the SICK cloud
  • Support via SICK Support Portal
  • Neuronal networks optimized for SICK products
  • Free trial offer on request
  • Deep Learning is part of the SICK AppSpace eco-system
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Intelligent Inspection
Intelligent Inspection
2D machine vision solution powered by deep learning
  • Classification of objects powered by deep learning technology
  • Runs on InspectorP62x Deep Learning 2D cameras
  • Easy-to-use user interface in web browser
  • Traditional rule-based machine vision software tools included
  • Quick customization with SICK Nova Tools
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For Increased Efficiency, Deep Learning is the Future
Jan 16, 2020
For Increased Efficiency, Deep Learning is the Future
Machines are learning to think. Deep learning is a machine learning technique − and the most significant future technology in artificial intelligence. SICK transfers this key technology to its... Read on
SICK’s growth continues in 2018 - Investments in Start-Up Initiatives pay off
Apr 30, 2019
Waldkirch, 30 April 2019 – SICK achieved above-average growth in sales again during the 2018 fiscal year, measured against the growth rate of Germany’s engineering sector. Orders received exceeded... Read on
The chancellor visits SICK – Deep learning wows Merkel and Löfven at the Hannover Messe 2019
Apr 4, 2019
The chancellor visits SICK – Deep learning wows Merkel and Löfven at the Hannover Messe 2019
Deep learning is one of the SICK presentation topics at the Hannover Messe 2019. The chancellor was personally very impressed with this and other aspects of the advancing Industry 4.0 applications. During... Read on
Axle Counter
Out and about with SICK: Four thematic routes at the SPS 2019
Nov 27, 2019
Out and about with SICK: Four thematic routes at the SPS 2019
SICK supplies a wide range of solutions for logistics, process and factory automation along the value-adding chain. On behalf of the many other industries and complete solutions, SICK has selected four... Read on
SICK reaches forecast targets for 2019 - Solid growth and major investments in research and development
Apr 29, 2020
SICK reaches forecast targets for 2019 - Solid growth and major investments in research and development
Waldkirch, 29 April 2020 – SICK continued growing in a challenging market environment. Group sales by the sensor producer increased by 7 percent to EUR 1,750.7 million during the 2019 fiscal year... Read on
4.0 NOW – SICK will be fully networked at the Hannover Messe 2019
Feb 27, 2019
4.0 NOW – SICK will be fully networked at the Hannover Messe 2019
The time has arrived: Industry 4.0 is happening now. SICK will show what this looks like at the Hannover Messe 2019 from 1 to 5 April 2019 with a live stream from the 4.0 NOW Factory in Freiburg. The official... Read on
dStudio
dStudio
SICK AppSpace Artificial Intelligence
Deep Learning
  • Description: DStudio is a SICK web service that can be used to train neuronal networks which are optimized for various SICK devices. Thanks to the intuitive user interface, it can be used even without sound AI knowledge. Progress and success of the training are shown in clear graphics so the neuronal network can be assessed before it is put into productive operation.
  • Note: DStudio can be found at dstudio.cloud.sick.com. Please use your SICK ID for login.
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Interview about 4.0 NOW factory: Combining innovations
Jun 2, 2020
Interview about 4.0 NOW factory: Combining innovations
SICK opened the gates to the 4.0 NOW factory in Freiburg in 2019. Since then, not only have groups of visitors gained exciting insights into production there, but also Joachim Schultis, Head of Operations... Read on
Deep Learning

Type: Product family overview

Part number: -

Title: Deep Learning

Release date: Jan 30, 2021

Size: 320.54 KB

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SICK AppSpace

Type: Special information

Part number: 8019161

Title: SICK AppSpace

Release date: Nov 12, 2018

Size: 3.37 MB

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