Video/Webinars
Webinar "Towards Transparent, Safe and Trustworthy AI for critical infrastructures"
This webinar focuses on the development of safe, explainable, and algorithmically transparent methods as part of the AI4REALNET project.
Video/Webinars
Webinar: Knowledge-Assisted AI Applications for Real-World Network Infrastructure
This webinar showcases how the AI4REALNET project is driving innovation in critical infrastructure through advanced AI applications.
Article/Books/eBooks
Uncertainty-Based Learning of a Lightweight Model for Multimodal Emotion Recognition
In this paper, the authors propose a lightweight neural network architecture that extracts and performs the analysis of multimodal information using the same audio and visual networks across multiple temporal segments.
White paper
Position paper on AI for the operation of critical energy and mobility network infrastructures
This position paper outlines AI4REALNET’s approach to applying AI in network infrastructure operations, translating application needs into algorithmic proposals for effective human-AI collaboration in decision-making processes.
Software resources
CO2A – Contrastive Conditional domain Alignment
A novel unsupervised domain adaptation approach for action recognition from videos, inspired by recent literature on contrastive learning.
Software resources
Augmentation-free unsupervised approach for point clouds
Unsupervised learning on 3D point clouds has undergone a rapid evolution, especially thanks to data augmentation-based contrastive methods.