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''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.'' | [[File:EN FundedbytheEU RGB POS.png|middle|frameless|upright=0.1|link=|alt=]]''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.'' | ||
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Revision as of 07:20, 10 May 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
- In the Landscape Analysis you can find all the background research on areas adjacent to Edge AI and Industry 5.0
- The AI Reference Implementations section contains existing useful material compiled by the AI REDGIO 5.0 to help you kickstart your manufacturing AI experiments
- All AI REDGIO 5.0 Enabling Tools at your disposal for trial and use
Asset Categories
Find assets based on the categories of your interest
Latest
The latest assets added to our reference AI implementations portfolio
- AI REDGIO 5.0 Smart Data Enabler
- AM Tomography Image Processing Algorithm
- Tabular-data Rehearsal-based Incremental Lifelong Learning Framework (TRIL3)
- Cream Cheese Production and Quality Dataset
- Acceleration Datasets
About AIREDGIO 5.0
Visit the official AI REDGIO 5.0 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. 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.