Displaying 8 resources
Article/Books/eBooks Article/Books/eBooks

Human-computer intra-action: a relational approach to digital media and technologies

The growing pervasiveness of digital technologies has exposed the entanglements of Human-Computer Interaction (HCI) with its surrounding context, from the immediate vicinity of interfaces to global issues.

Category
Multi-modal interaction, Technology methodologies and landscape
Target audience
ADR Experts and Associations, Private Sector, Researchers and Academic
Source
Adra-e
Tutorial/How To/Guides Tutorial/How To/Guides

Preparing action interaction data for training

If you use the Next-Best-Action custom recipe, Amazon Personalize uses action interactions data to identify user interest and predict the actions they will most likely take.

Category
Multi-modal interaction
Target audience
ADR Experts and Associations, Private Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

At-the-edge AI acceleration on FPGAs, from CNNs to SNNs

This paper outlines the initial FPGA-centric endeavors within the EdgeAI project, targeting scenarios where extremely constrained power-energy parameters intersect with the demand for high performance and accuracy in executing Artificial Intellige

Category
Edge-based AI
Target audience
ADR Experts and Associations, Individual Citizens/Members of the Society, Private Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

Comparing implementations of a Small CNN on Commodity Hardware

Presentation detailing our benchmarking of several low cost boards for AI inference on the Edge.
The NN is a small NN that performs 1 channel images classification over 58 categories targeting an industrial application.

Category
Edge-based AI
Target audience
ADR Experts and Associations, Individual Citizens/Members of the Society, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e
Article/Books/eBooks Article/Books/eBooks

Edge AI trends and engineering principles applied to micro, meta, and end-to-end AI system verification, validation, and testing

Edge AI, which refers to the deployment of edge computing and artificial intelligence (AI) models and algorithms on edge devices like IoT devices and embedded systems, is rapidly evolving with several emerging trends and engineering principles app

Category
Edge-based AI
Target audience
Individual Citizens/Members of the Society, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e

EdgeAI

Develop new electronic components and systems, processing architectures, connectivity, software, algorithms, and middleware through the combination of microelectronics, AI, embedded systems, and edge computing.

Category
Edge-based AI
Target audience
Individual Citizens/Members of the Society, Policy Makers, Private Sector, professionals, Public Sector, Researchers and Academic
Source
Adra-e