Objectives
Primary Objectives
The primary objective of the FAST-EO project is to enhance the accessibility and democratization of foundation models (FMs) within the EO community. This includes:
Define and develop an EO-specific Foundation Model
Specify and explore EO use-cases benefiting from Foundation Model
Develop AI4EO applications derived from Foundation Model
Assess impacts of AI4EO Foundation models and define Roadmap
Foster community development of EO Foundation Model users / providers
Outcomes
Tailoring to Data Domains
Adapting FMs specifically for synthetic aperture radar (SAR), multispectral, and hyperspectral sensor characteristics, and considering the multi-temporal nature of EO data, with a focus on prioritizing existing European missions such as Sentinels, while also aligning with upcoming initiatives such as the Copernicus Hyperspectral Imaging Mission of ESA (CHIME).
Enhanced Multimodality
Incorporating text-based, semantic masking-based or geometrical prompts to enhance multimodality beyond just sensor data.
Overcoming Computational Barriers
Addressing computational limitations to facilitate the optimal reconfiguration and refinement of FMs for various EO tasks, thereby encouraging their widespread adoption in practical applications.
Affordable Fine-Tuning
Design and train FM's on world-wide samples, with the objective to reduce the number of labelled data for novel down-stream tasks, which can be deployed at a global scale.
Operational and Accessible Implementation
Devising strategies for effectively scaling up and moving towards the operationalization of these FMs. Additionally, ensuring their accessibility for non-technical audiences, facilitated by both our project consortium members and our project stakeholders.
