ADR Awareness Centre | Adra Association

The European AI, Data and Robotics stakeholders operate from diverse historic backgrounds. To tap into the potentials of the diverse knowledge and resources generated in the AI, Data, and Robotics ecosystem, an all-inclusive collaboration approach between these stakeholders is necessary to make the ADR resources available and accessible to all.

For this, the ADR Awareness Centre is developed as an open repository of ADR educational resources and materials to enable collaboration and alignment among all projects within the Partnership, relevant external projects, and the public. The Awareness Centre will collect, validate, and publish educational resources and materials related to AI, Data, and Robotics.

- Who is this for? Everyone. Every project and organization in Europe including the general member of the public
- What does this Centre provide? AI, Data, and Robotics educational resources and materials produced in the EU
- When a new resource becomes available? The list of the resources will be updated when a new resource is submitted and validated
- Why should I publish a resource? Firstly, publishing your materials will promote and make them accessible to all. Secondly, it increases the transparency of your work and improves your and your organizations reputation. Last but not the least, your material will help address ADR challenges and contribute to shaping the future of ADR in Europe.
- How can I contribute and publish my resources? The Centre designed a very simple process for you to submit and publish your resources. You only need to submit your resource here and we will review and get it published and publicly accessible to all.
- What kinds of resources can I publish? The Centre only collects and publishes ADR related educational resources that can be publicly available and accessible to all. Copyrighted and licensed contents will not be published in the Centre.

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Displaying 273 resources

Distance-based Classification

This lecture overviews Distance-based Classification that has many applications in classification. It covers the following topics in detail: k-Nearest neighbor classification, Nearest neighbor graphs Supervised Learning Vector Quantization, LVQ1/2/3.

Category

Systems, methodologies, hardware, and tools

Source

AI-OnDemand

Digital Image Formation

This lecture overviews Image Formation, which is of primary importance in ensuring image quality and enabling image processing. It covers the following topics in detail: Light reflection models. Camera structure and models, e.g., Pinhole Camera.

Category

Systems, methodologies, hardware, and tools

Source

AI-OnDemand

Multiple Drone Media Production

This lecture overviews Multiple Drone Media Production that has many applications in drone cinematography.

Category

Systems, methodologies, hardware, and tools

Source

AI-OnDemand

Autonomous Car Sensors

This lecture overviews Autonomous Car Sensors that has many applications in autonomous car perception.

Category

Systems, methodologies, hardware, and tools

Source

AI-OnDemand

Dimensionality Reduction

This lecture overviews Dimensionality Reduction that has many applications in object clusring and object recognition. It covers the following topics in detail: Feature selection. Principal Component Analysis. Linear Discriminant Analysis.

Category

Systems, methodologies, hardware, and tools

Source

AI-OnDemand

Motion Estimation

Motion estimation principals will be analyzed. Initiating form 2D and 3D motion models, displacement estimation as well as quality metrics for motion estimation will subsequently be detailed.

Category

Systems, methodologies, hardware, and tools

Source

AI-OnDemand