XMANAI Hybrid 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.
Welcome to the AI Assets Catalog! Here you can browse, search and download all the assets currently indexed in the AI-on-Demand platform, including AI libraries, datasets, containers, and more. You are welcome to publish your own AI assets here! To do so, log in in to the platform, go to your dashboard and use the Submit new content button to access the submission forms.
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.
A route prediction model geared towards enhancing safety of autonomous ships by supporting remote control center situation awareness.
A model capable of detecting anomalous ship behavior for a given geographical region.
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...
Python implementation of the VCRA/F model from the paper "Collision Risk Assessment and Forecasting on Maritime Data"
Pixel-level classification model, using the pixel-level classification bootstrapping service of AI4Copernicus project
Pixel-level classification model, using the pixel-level classification bootstrapping service of AI4Copernicus project
Pixel-level classification model, using the pixel-level classification bootstrapping service of AI4Copernicus project
Pixel-level classification model, using the pixel-level classification bootstrapping service of AI4Copernicus project
The model was designed for tree-crops semantic-segmentation and created using the AI4Copernicus service: “Deep network for pixel-level classification of S2 patches"