EGU23-4929, updated on 04 Jan 2024
https://doi.org/10.5194/egusphere-egu23-4929
EGU General Assembly 2023
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Using AI and ML to support marine science research

Ilaria Fava1, Peter Thijsse2, Gergely Sipos1, and Dick Schaap2
Ilaria Fava et al.
  • 1EGI Foundation, Communications Team, Amsterdam, Netherlands (ilaria.fava@egi.eu)
  • 2Maris

The iMagine project is devoted to developing and delivering imaging data and services for aquatic science. Started in September 2022, the project will provide a portfolio of image data collections, high-performance image analysis tools empowered with Artificial Intelligence, and best practice documents for scientific image analysis. These services and documentation will enable better and more efficient processing and analysis of imaging data in marine and freshwater research, accelerating our scientific insights about processes and measures relevant to healthy oceans, seas, and coastal and inland waters. By building on the European Open Science Cloud compute platform, iMagine delivers a generic framework for AI model development, training, and deployment, which researchers can adopt for refining their AI-based applications for water pollution mitigation, biodiversity and ecosystem studies, climate change analysis and beach monitoring, but also for developing and optimising other AI-based applications in this field. The iMagine AI development and testing framework offers neural networks, parallel post-processing of extensive data, and analysis of massive online data streams in distributed environments. The synergies among the eight aquatic use cases in the project will lead to common solutions in data management, quality control, performance, integration, provenance, and FAIRness and contribute to harmonisation across RIs. The resulting iMagine AI development and testing platform and the iMagine use case applications will provide another component to the European marine data management landscape, valid for the Digital Twin of the Ocean, EMODnet, Copernicus, and international initiatives. 

How to cite: Fava, I., Thijsse, P., Sipos, G., and Schaap, D.: Using AI and ML to support marine science research, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4929, https://doi.org/10.5194/egusphere-egu23-4929, 2023.