Autoencoder-Based Maritime Anomaly Detection
A model capable of detecting anomalous ship behavior for a given geographical region.
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.
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"
NN-SPM estimates ship fuel consumption taking into consideration weather and operational conditions.
LexaTexer provides an Enterprise AI platform to support the energy value chain with prebuilt, configurable AI applications addressing CAPEX intense hydro assets like Pelton and Francis turbines and pumps. In this project we combine our Enterprise AI platf...