iMagine: Empowering Aquatic Research through AI-Driven Tools for Imaging Data Analysis

iMagine platform offers AI-driven tools aimed at enhancing the processing and analysis of imaging data in both marine and freshwater research. These tools facilitate the study of processes crucial for the health of oceans, seas, coastal, and inland waters. Leveraging the European Open Science Cloud (EOSC), iMagine project [1] provides a framework for developing, training, and deploying AI models. Aquatic researchers utilize this framework to refine AI applications for various purposes, including water pollution mitigation, biodiversity studies, climate change analysis, and beach monitoring.

The project integrates neural networks, parallel post-processing of large data, and analysis of online data streams in distributed environments. Thirteen research infrastructures (RIs) share millions of images and AI applications through the iMagine framework. Collaboration among these RIs and IT experts results in the development of best practices for delivering image processing services. The project establishes common solutions in data management, quality control, performance, integration, and FAIRness across RIs, thereby promoting harmonization and providing input for best practice guidelines.
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To effectively fulfill the project's objectives, eight distinct use cases across various domains of aquatic science actively collaborate with the providers of the iMagine Platform. This collaborative partnership involves joint efforts to leverage the capabilities of the iMagine Platform, foster innovation, and amplify the collective impact on advancing image analysis tools and services for environmental monitoring and management within the realm of aquatic research. These projects encompass a range of activities including the collection, storage, analysis, and processing of diverse imagery sources.

The platform allows users to develop, train, and share AI models on its marketplace [2]. These models are encapsulated as Docker images to ensure their reproducibility. Researchers benefit from the platform's flexibility, which enables seamless execution of these Docker containers on both federated clouds of the European Grid Infrastructure (EGI) e-infrastructure and High-Performance Computing (HPC) infrastructures.

References
[1] https://www.imagine-ai.eu
[2] https://dashboard.cloud.ai4eosc.eu/marketplace