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 Copyrighted and licensed contents will not be published in the Centre.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 302 resources

Syntactic Pattern Recognition

This lecture overviews that has many applications in data analysis. It covers the following topics in detail: Syntactic Pattern Recognition Systems. Preprocessing Techniques. String-Based Models.

Category

Data for AI, Systems, methodologies, hardware, and tools

Source

AI-OnDemand

Digital Image Processing

This lecture overviews Digital Image Processing that has many applications in improving image visual quality.

Category

Systems, methodologies, hardware, and tools

Source

AI-OnDemand

Digital Image Compression

This lecture overviews Digital Image Restoration that has many applications in scientific/medical imaging and in digital photography.

Category

Systems, methodologies, hardware, and tools

Source

AI-OnDemand

Finite Element Method for Stress Analysis

This lecture overviews Finite Element Method for Stress Analysis that has many applications in Mechanical and Civil engineering, in Material Science and Biomedicine.

Category

Systems, methodologies, hardware, and tools

Source

AI-OnDemand

Human Visual System

This lecture overviews the Human Visual System that has many applications in understanding image perception and image quality issues. It covers the following topics in detail: Human Visual System (eyes and visual pathway, stereo vision).

Category

Systems, methodologies, hardware, and tools

Source

AI-OnDemand

NLP and Text Sentiment Analysis

This lecture overviews Natural Language Processing (NLP) and Text Sentiment Analysis that has many applications in Text Analytics, Opinion extraction, Opinion mining, Sentiment mining, Subjectivity analysis.

Category

Systems, methodologies, hardware, and tools

Source

AI-OnDemand