The AIOPEN project will combine and extend the existing platform ASB (Automated Service Builder), EOPEN (Open Interoperable Platform for Unified Access & Analysis of EO Data) and EOEPCA (EO Exploitation Platform Common Architecture) with new and innovative services based on operationally mature AI/ML software capabilities to provide a platform that supports the end-to-end AI model …
The primary objective of this project is to augment the capabilities of Ellip-powered Exploitation platforms, specifically Geohazards Exploitation Platform (GEP) and Urban Thematic Exploitation Platform (U-TEP), by seamlessly integrating an AI/ML processing framework. This comprehensive framework will encompass the entire machine learning pipeline, including data discovery, access to training data, model development and deployment. GEP …
Development of AI based methods to classify herds of different animals based on the spatial distribution patterns adopted within different herd species. AI based pattern recognition methods based on distribution patterns of animals within a herd detected in EO imagery.
Illegal excavation of archaeological sites aimed at collecting historical material culture (‘looting’) to introduce it in the illicit market of antiquities is a pressing problem on a global scale. Under favourable circumstances, looting can be exposed on Earth Observation (EO) data by detecting changes that have occurred between two or more consecutive EO images of …
Introduction and Objectives The European Space Agency, ESA, is organising the EO Science for Society Info Days to introduce activities in FutureEO-1 Segment 2 Block 4 “EO Science for Society”. The main goals of these Info Days will be to present the upcoming opportunities for European entities to participate in the activities of the ongoing …
The project is dedicated to demonstration of Privacy Preserving Machine Learning (PPML) in EO data analytics as an emerging field in data science that strives to address protecting data privacy and confidentiality in a variety of machine learning applications. It is aimed to research and demonstrate secure frameworks for AI/ML, including cryptographic techniques such as …
The project aims at the development of algorithms for cross-calibration of hyperscout with S-2 and the development of the phi-sat 1 brain for cloud detection. The team is assessing Machine Learning methodology, techniques, and a suite of applications (ranging from Radiometric calibration of a single band L2A data, Calibration of data products, e.g. NDVI or …
The GRD4ML project aims to create an Enhanced Environment to generate Reference Data for the Retrieval of Geophysical Parameters by Machine Learning. Scientist and application developers will have the opportunity to create, enhance, utilise and manage their own datasets for training neural networks in a integrated environment based on free licensed tools and cloud computing …
An unprecedented richness of data is captured by satellites every day, resulting in an ever-growing time series of EO data. Despite the extensive availability of data, there are still many challenges when defining procedures for extracting relevant information from long time series. The goal of the AI4FOOD project is to tackle the challenges that arise …
