Jump to content

Main Page: Difference between revisions

 
(8 intermediate revisions by the same user not shown)
Line 28: Line 28:


== About AIREDGIO 5.0 ==
== About AIREDGIO 5.0 ==
Visit the official [https://www.airedgio5-0.eu/ AI REDGIO 5.0 website] to find out more about the project.
Visit the official [https://www.airedgio5-0.eu/ AI REDGIO 5.0 project website] to find out more about the project.


=== Acknowledgement ===
=== Acknowledgement ===
<p style="font-size:90%;line-height: 1.5em">
<p style="font-size:90%;line-height: 1.5em">
''This wiki has been created in the context of the AI REDGIO 5.0 “Regions and (E)DIHs alliance for AI-at-the-Edge adoption by European Industry 5.0 Manufacturing SMEs” EU Innovation Action Project under Grant Agreement No 101092069. Ai REDGIO 5.0 is funded by the European Union. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or Health and Digital Executive Agency (HaDEA). Neither the European Union nor HaDEA can be held responsible for them.''
''This wiki has been created in the context of the AI REDGIO 5.0 “Regions and (E)DIHs alliance for AI-at-the-Edge adoption by European Industry 5.0 Manufacturing SMEs” EU Innovation Action Project under Grant Agreement No 101092069.''
</p>

Latest revision as of 07:25, 24 June 2025

Welcome to the AI REDGIO 5.0 Edge AI Reference Implementations for Industry 5.0

A compilation of reference implementations of Edge AI models and assets in manufacturing business cases, coming from open-source initiatives, the AI REDGIO 5.0 partners’ background and experience, but also complemented by specific Edge AI models and pipelines created in the AI REDGIO 5.0 project to address concrete problems on which the experiments focus.

Getting started

Asset Categories

Find assets based on the categories of your interest


Latest

The latest assets added to our reference AI implementations portfolio

  1. AI REDGIO 5.0 Smart Data Enabler
  2. AM Tomography Image Processing Algorithm
  3. Tabular-data Rehearsal-based Incremental Lifelong Learning Framework (TRIL3)
  4. Cream Cheese Production and Quality Dataset
  5. Acceleration Datasets

About AIREDGIO 5.0

Visit the official AI REDGIO 5.0 project website to find out more about the project.

Acknowledgement

This wiki has been created in the context of the AI REDGIO 5.0 “Regions and (E)DIHs alliance for AI-at-the-Edge adoption by European Industry 5.0 Manufacturing SMEs” EU Innovation Action Project under Grant Agreement No 101092069.