Localized image editing through joint factorization of parts of appearances in pre-trained GANs. read more of PandA: Unsupervised Learning of Parts and Appearances in the Feature Maps of GANs

A neural network-based time-series forecasting model for concentrations of an electrochemical reaction. read more of S-X-AIPI Pharma Use Case Process Model

A method for controlling diversity between clusterings in deep clustering frameworks. read more of DivClust: Controlling Diversity in Deep Clustering

Learning Visual Explanations for DCNN-Based Image Classifiers Using an Attention Mechanism read more of L-CAM

A lightweight AI rerouting decision model that helps to determine whether running weather routing is beneficial. The goal of the model is to help minimize the high computational workload demanded by a commercial weather routing system that performs freque... read more of Weather rerouting decision support model

EU-funded XMANAI project deals with bringing explainable AI to the Industry, and this asset is an example of the models developed during the project. read more of XMANAI Hybrid model

A route prediction model geared towards enhancing safety of autonomous ships by supporting remote control center situation awareness. read more of Maritime Route Prediction for Remote Control Centre Decision Support

A model capable of detecting anomalous ship behavior for a given geographical region. read more of Autoencoder-Based Maritime Anomaly Detection

Digital twins are computational models that replicate the structure, behaviour and overall characteristics of a physical asset in the digital world. In the maritime domain, conventional approaches have relied on mathematical modeling (e.g., linearised equ... read more of Data driven digital twins for the maritime domain

Python implementation of the VCRA/F model from the paper "Collision Risk Assessment and Forecasting on Maritime Data" read more of Vessel Collision Risk Assessment and Forecasting (VCRA/F)