
Holistic framework for AI in critical network infrastructures
This document establishes the main foundations of the AI4REALNET project, in particular, the following key outcomes: - The formal specification of domain-specific use cases (UCs), replicating real-world operating scenarios involving human operator

Real-Time Context-Aware Microservice Architecture for Predictive Analytics and Smart Decision-Making
This paper aims at proposing a scalable architecture to provide real-time context-aware actions based on predictive streaming processing of data as an evolution of a previously provided event-driven service-oriented architecture which already perm

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.

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.

VISIONE Feature Repository for VBS: Multi-Modal Features and Detected Objects from MVK Dataset
This repository contains a diverse set of features extracted from the marine video (underwater) dataset (MVK) .

A deep learning-based dataset of WFA-positive perineuronal nets and parvalbumin neurons localizations in the adult mouse brain
This dataset contains high-resolution images for the visualization of perineuronal nets (PNNs) and parvalbumin-expressing (PV) cells. The dataset contains microscopy images of coronal brain slices from 7 adult mice.