
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.

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.

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.

Data Storytelling and Big Data value chain in Natural Disaster Management
This lecture explores the concepts of Data Storytelling and the Big Data value chain in the context of Natural Disaster Management.

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.

ToDY: Time of Day/Year: Dataset for visual time of day and season classification
The dataset provides training and valiation data for classifying images by time of day and season (time of year). The images are taken from the Skyfinder dataset, containing webcam images along with timestamps and geolocation.