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.
This dataset contains a set of georeferenced labels used in the LIVE4ENV project for training and evaluating an AI model for land-cover classification in livestock farms. It includes 3 classes: - 0: non-productive areas - 1: woodland - 2: pasture
This dataset contains corrected PM10 measurements for Sofia Jan-May 2022 fetched from Sensor Community and calibrated with an Extremely Randomised Tree.
Climate change, with its accompanying global warming and increasingly severe weather conditions, presents substantial risks to agricultural sustainability worldwide. This is driving the agri-food sector to adapt through the use of new technologies and str...
A dataset of the Montenegro electricity generation by generation unit for the whole year 2022, on an hourly basis.
Data storage of Piva, Krupac and Slano, Montenegro water reservoirs during 2022.
Small dataset with the days that were Holiday on Montenegro on an hourly basis in 2022.
This dataset contains data of electricity generation of Montenegro and several neighboring countries between 2019 and mid 2023. Data was gathered from the ENTSOE transparency platform.
This dataset contains a set of samples used in the EO4NOWCAST project to train a ML model to predict current soil moisture map in a Area of Interest (in this case, Genoa basin in Italy). Soil Moisture estimation is a crucial parameter for prediction of fl...
This metadata document provides information about the Soil Productivity Map. This map was generated following the methodology presented in Schaetzl, R. J., Krist Jr, F. J., & Miller, B. A. (2012). A taxonomically based ordinal estimate of soil productivit...
Agriculture productivity maps based on satellite images and machine learning algorithms have become powerful tools for understanding and optimizing agricultural practices. By combining the capabilities of satellite imagery and machine learning algorithms,...