Article/Books/eBooks
EdgeAI: Leveraging SNNs, Transformers, and Autoencoders for Near-Sensors Intelligence
This talk will explore the cutting-edge advancements in EdgeAI for biosignal analysis, focusing on innovative algorithms such as Spiking Neural Networks (SNNs), Transformers, and Autoencoders.
Article/Books/eBooks
Functional and Non-Functional Requirements in Edge Ai Systems
This presentation highlights the critical elements defining edge AI solutions’ performance and effectiveness.
Article/Books/eBooks
Pioneering the Future of Edge AI
In today’s fast-evolving technological landscape, edge AI stands at the forefront of innovation, enabling data processing at the edge, closer to the source of information.
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
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.
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