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 Copyrighted and licensed contents will not be published in the Centre.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 83 resources

ECG Signal Analysis

This lecture overviews ECG Signal Analysis as well as other cardiology imaging methods that has many applications in cardiological disorder diagnosis and treatment. It covers the following topics in detail: Background nnowledge of ECG Signals.

Category

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

Source

AI-OnDemand

Multilayer perceptron. Backpropagation

This lecture covers the basic concepts and architectures of Multi-Layer Perceptron (MLP), Activation functions, and Universal Approximation Theorem.

Category

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

Source

AI-OnDemand

Fast 3D Convolution algorithms

This lecture overviews Fast 3D Convolution algorithms that has many applications in the fast implementation of 3D image and video filtering, 3D CNNs and motion estimation.

Category

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

Source

AI-OnDemand

Convolutional Neural Networks Lecture

Convolutional Neural Networks form the backbone of current AI revolution and are used in a multitude of classification and regression problems. This lecture overviews the transition from multilayer perceptrons to deep architectures.

Category

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

Source

AI-OnDemand

Fast 1D Convolution Algorithms

1D convolutions are extensively used in digital signal processing (filtering/denoising) and analysis (also through CNNs). As their computational complexity is of the order O(N^2), their fast execution is a must. This lecture will overview

Category

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

Source

AI-OnDemand

Graph Convolutional Networks

This lecture overviews Graph Convolutional Networks (GCN) that have many applications in Deep Learning, Signal and Video Analysis, Network Theory, Web Science and Social Media Analytics. It covers the following topics in detail: Graph Convolutions.

Category

Data for AI

Source

AI-OnDemand