# Final Symposium

Date: 21 July 2022
Location: Aula VIVES Hogeschool, Xaverianenstraat 10, 8000 Brugge
(Deprecated) Registration page

• Attendees:
  • Kris Bellemans (E.D.&A.)
  • Wouter Reusen (Melexis Technologies nv)
  • Luc Buydens (Melexis Technologies nv)
  • Stefan Schulte (Teledyne FLIR)
  • Robbe Goetehals (Citymesh)
  • Koen Vandeputte (Citymesh)
  • Michel Dequick (Teledyne FLIR)
  • Kevin Vandecasteele (Fanuc Benelux)
  • Nicolas Maes (Picanol)
  • Paschalis Tsiaflakis (Nokia Bell Labs)
  • Marcel Verhoeven (CNHi)
  • Karen Feyen (Thomas More Hogeschool)
  • Geert Vanstraelen (Macq)
  • Wim Glorieux (Chilli Robotics nv)
  • Thomas Nauwelaerts (NiniX Technologies)
  • Michel Hillen (Atlas Copco)
  • Carl Declercq (TVH Parts Waregem)
  • Robbe Fouvry (AVR)
  • Pieter Verstraete (AVR)
  • Frederik De Vusser (VLAIO)
  • Maarten Vanhoucke (Vanhoucke Machine Engineering)
  • Pedro Calleeuw (VIVES)
  • Freja Gheysen (VIVES)
  • Steven Hollevoet (VIVES)
  • Peter Vanbiervliet (VIVES)
  • Nico De Witte (VIVES)
  • Ruben Buysschaert (VIVES)
  • Geert Calu (VIVES)
  • Steve Simons (VIVES)
  • Griet Verbeke (VIVES)
  • Astrid Stroobandt (VIVES)
• Project team members:
  • Toon Goedemé (KU Leuven - De Nayer)
  • Kristof Van Beeck (KU Leuven - De Nayer)
  • Maarten Vandersteegen (KU Leuven - De Nayer)
  • Sille Van Landschoot (VIVES)
  • Jonas Lannoo (VIVES)

# Presentation Slides

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Final symposium slides

# Description

The final symposium has been organised for the broad public in the Aula of the VIVES Campus in Bruges. The event was advertised as "Artificial Intelligence, not in the Cloud, but on a microcontroller!". Nowadays we see and hear that AI is embedded in all sorts of devices and technologies: it runs on your smartphone to enhance camera images, Google uses it to improve your search results... All of that is quite usefull, but those applications require a lot of computational power and an internet connection! What if we want to deploy AI algorithms without taking the risk that our data is publicly available and without requiring that computational power? We have to do it on the system itself!

During the project we investigated the possiblities to deploy Deep Learning algorithms on systems that are not so computationaly strong, that are very energy efficient, and less dependent on a network. The results were combined in a manual of best practices and were applied on different use-cases from industry. In this symposium we submerge you in the world of AI and Deep Learning, applied on small electronic devices, such as a microcontroller. The symposium was concluded with a testimony from industry (Melexis) and a reception.

The symposium starts with the introduction of the project for attendees that are not member of the usergroup. Next, the workpackages and accompanying results were presented. The three academic use-cases and five industrial use-cases were discussed with the possibility to ask questions of the audience. The presentation slides are publicly provided. If you have any questions or are interested in working with us, please contact us via the contact details on the homepage.

# Event pictures