Pixel-level classification model for Sentinel-2 images based on processed images (bands 1,2,3,4 - labels 1,2,3)
Pixel-level classification model, using the pixel-level classification bootstrapping service of AI4Copernicus project
Earth observation plays a crucial role in supporting policy-making processes and developing some economic areas. A vast amount of earth observation data is collected that can feed AI models and methods and thus help to acquire new knowledge and develop innovative products. This section gives references on on-going projects and presents results in the area of AI in earth observation.
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 Security Bootstrapping services and resources have been developed in order to support the AI4Copernicus project’s open calls by reduce the time and resources of the bidders in the data preparation and allowing them to focus on the development of innov...
The Security Bootstrapping services and resources have been developed in order to support the AI4Copernicus project’s open calls by reducing the time and resources of the bidders in the data preparation and allowing them to focus on the development of inn...
The Security Bootstrapping services and resources have been developed in order to support the AI4Copernicus project’s open calls by reducing the time and resources of the bidders in the data preparation and allowing them to focus on the development of inn...
The Security Bootstrapping services and resources have been developed in order to support the AI4Copernicus project’s open calls by reducing the time and resources of the bidders in the data preparation and allowing them to focus on the development of inn...
The Security Bootstrapping services and resources have been developed in order to support the AI4Copernicus project’s open calls by reducing the time and resources of the bidders in the data preparation and allowing them to focus on the development of inn...
The model was designed for tree-crops semantic-segmentation and created using the AI4Copernicus service: “Deep network for pixel-level classification of S2 patches"
The dataset was designed for prediction of vegetation health on Sentinel-2 imagery and utilized in the AI4Copernicus service: “Long Short-Term Memory Neural Network for NDVI prediction" in which an LSTM neural network was trained in order to create an AI ...
The dataset was designed for semantic-segmentation-based deep learning models and utilized in the AI4Copernicus service: “Deep network for pixel-level classification of S2 patches" in which a U-net neural network was used in order to create an AI model fo...