Imaging data and services for aquatic science

HORIZON.1.3HORIZON-RIAID: 101058625
EC Contribution
€45,000
Consortium Size
24 orgs
Summary

iMagine provides a portfolio of free at the point of use image datasets, high-performance image analysis tools empowered with Artificial Intelligence (AI), and Best Practice documents for scientific image analysis. These services and materials 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 for healthy oceans, seas, coastal and inland waters. By building on the computing platform of the European Open Science Cloud (EOSC) the project delivers a generic framework for AI model development, training, and deployment, which can be adopted by researchers 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 compute layer consists of providers from the pan-European EGI federation infrastructure, collectively offering over 132,000 GPU-hours, 6,000,000 CPU-hours and 1500 TB-month for image hosting and processing. The iMagine AI framework offers neural networks, parallel post-processing of very large data, and analysis of massive online data streams in distributed environments. 13 RIs will share over 9 million images and 8 AI-powered applications through the framework. Having representatives so many RIs and IT experts, developing a portfolio of eye-catching image processing services together will also give rise to Best Practices. The synergies between aquatic use cases will lead to common solutions in data management, quality control, performance, integration, provenance, and FAIRness, contributing to harmonisation across RIs and providing input for the iMagine Best Practice guidelines. The project results will be integrated into and will bring important contributions from RIs and e-infrastructures to EOSC and AI4EU.

Consortium (24)

🇳🇱 STICHTING EGINL
coordinator
AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
partner
🇵🇹 ASSOCIACAO CNCA - CENTRO NACIONAL DE COMPUTACAO AVANCADAPT
partner
🇩🇪 DEUTSCHES FORSCHUNGSZENTRUM FUR KUNSTLICHE INTELLIGENZ GMBHDE
partner
🇮🇹 EUROPEAN MULTIDISCIPLINARY SEAFLOORAND WATER COLUMN OBSERVATORY - EUROPEAN RESEARCH INFRASTRUCTURE CONSORTIUM (EMSO ERIC)IT
partner
🇮🇹 FONDAZIONE CENTRO EURO-MEDITERRANEOSUI CAMBIAMENTI CLIMATICIIT
partner
🇫🇷 INSTITUT FRANCAIS DE RECHERCHE POUR L'EXPLOITATION DE LA MERFR
partner
🇮🇹 ISTITUTO NAZIONALE DI OCEANOGRAFIA E DI GEOFISICA SPERIMENTALEIT
partner
🇩🇪 KARLSRUHER INSTITUT FUER TECHNOLOGIEDE
partner
🇵🇹 LABORATORIO DE INSTRUMENTACAO E FISICA EXPERIMENTAL DE PARTICULAS LIPPT
partner
🇳🇱 MARIENE INFORMATIE SERVICE MARIS BVNL
partner
🇮🇪 MARINE INSTITUTEIE
partner
🇬🇷 NATIONAL INFRASTRUCTURES FOR RESEARCH AND TECHNOLOGYGR
partner
🇪🇸 ORBITAL EOS SLES
partner
🇪🇸 SOCIB - CONSORCIO PARA EL DISENO, CONSTRUCCION, EQUIPAMIENTO Y EXPLOTACION DEL SISTEMA DE OBSERVACION COSTERO DE LAS ILLES BALEARSES
partner
🇫🇷 SORBONNE UNIVERSITEFR
partner
🇮🇪 SOUTH EAST TECHNOLOGICAL UNIVERSITYIE
partner
🇹🇷 TURKIYE BILIMSEL VE TEKNOLOJIK ARASTIRMA KURUMUTR
partner
🇮🇹 UNIVERSITA DEGLI STUDI DI TRENTOIT
partner
🇪🇸 UNIVERSITAT POLITECNICA DE CATALUNYAES
partner
🇪🇸 UNIVERSITAT POLITECNICA DE VALENCIAES
partner
🇫🇷 UNIVERSITE DE LORRAINEFR
partner
🇸🇰 USTAV INFORMATIKY SLOVENSKEJ AKADEMIE VIED, VEREJNA VYSKUMNA INSTITUCIASK
partner
🇧🇪 VLAAMS INSTITUUT VOOR DE ZEEBE
partner

Project Results (41)

Source: CORDIS, the EU research results database.

Publications (16)
Automated image classification workflow for phytoplankton monitoring
Frontiers in Marine Science· 2025DOI
Wout Decrop, Rune Lagaisse, Jonas Mortelmans, Carlota Muñiz, Ignacio Heredia, Amanda Calatrava and Klaas Deneudt
Best practices for AI-based image analysis applications in aquatic sciences: The iMagine case study
Ecological Informatics· 2025DOI
Elnaz Azmi, Khadijeh Alibabaei, Valentin Kozlov, Tjerk Krijger, Gabriele Accarino, Sakina-Dorothée Ayata, Amanda Calatrava, Marco Mariano De Carlo, Wout Decrop, Donatello Elia, Sandro Luigi Fiore, Marco Francescangeli, Jean-Olivier Irisson, Rune Lagaisse, Martin Laviale, Antoine Lebeaud, Carolin Leluschko, Enoc Martínez, Germán Moltó, Igor Ruiz Atake, Antonio Augusto Sepp Neves, Damian Smyth, Jesús Soriano-González, Muhammad Arabi Tayyab, Vanessa Tosello, Álvaro López García, Dick Schaap, Gergely Sipos
Blending physical and artificial intelligence models to improve satellite-derived bathymetry mapping
Ecological Informatics· 2025DOI
Daniel García-Díaz, Sandra Paola Viaña-Borja, Mar Roca, Gabriel Navarro, Isabel Caballero
iMagine: AI-Powered Image Data Analysis in Aquatic Science
Proceedings of the Platform for Advanced Scientific Computing Conference· 2025DOI
Elnaz Azmi; Khadijeh Alibabaei; Valentin Kozlov; Álvaro López García; Dick Schaap; Gergely Sipos
iMagine: Revolutionising Aquatic Sciences with AI-Driven Image Analysis
ERCIM News· 2025DOI
Sipos, Gergely, Schaap, Dick
Improving oil slick trajectory simulations with Bayesian optimization
Ecological Informatics· 2025DOI
Gabriele Accarino, Marco M. De Carlo, Igor Ruiz Atake, Donatello Elia, Anusha L. Dissanayake, Antonio Augusto Sepp Neves, Juan Peña Ibañez, Italo Epicoco, Paola Nassisi, Sandro Fiore, Giovanni Coppini
Transfer Learning for Distance Classification of Marine Vessels Using Underwater Sound
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing· 2025DOI
Wout Decrop, Klaas Deneudt, Clea Parcerisas, Elena Schall, Elisabeth Debusschere
“UDE DIATOMS in the Wild 2024”: a new image dataset of freshwater diatoms for training deep learning models
GigaScience· 2024DOI
Aishwarya Venkataramanan, Michael Kloster, Andrea Burfeid-Castellanos, Mimoza Dani, Ntambwe A S Mayombo, Danijela Vidakovic, Daniel Langenkämper, Mingkun Tan, Cedric Pradalier, Tim Nattkemper, Martin Laviale, Bánk Beszteri
AI-based fish detection and classification at OBSEA underwater observatory
International Conference on Marine Data and Information Systems - Proceedings Volume· 2024
Oriol Prat Bayarri, Pol Baños Castelló, Enoc Martinez, Joaquin del Rio
Big Data Deduplication in Data Lake
Acta Polytechnica Hungarica· 2024DOI
Jakub Hlavačka; Martin Bobák; Ladislav Hluchý
Deep Learning Based Characterization of Cold-Water Coral Habitat at Central Cantabrian Natura 2000 Sites Using YOLOv8
Journal of Marine Science and Engineering· 2024DOI
Alberto Gayá-Vilar, Alberto Abad-Uribarren, Augusto Rodríguez-Basalo, Pilar Ríos, Javier Cristobo, Elena Prado
DETECT AND FOLLOW A CUSTOM OBJECT, USING OBSEA UNDERWATER CRAWLER
MARTECH 2024 - Mallorca (Spain)· 2024
Ahmad Falahzadeh, Daniel Mihai Toma, Marc Nogueras, Enoc Martines, Matias Carandell, Jacopo Aguzzi and Joaquín del Río
TOOLS FOR ECOSYSTEM MONITORING BASED ON FISH DETECTION AND CLASSIFICATION USING DEEP NEURAL NETWORKS
MARTECH 2024 - Mallorca (Spain)· 2024
Oriol Prat, Pol Baños, Enoc Martinez, Joaquin del Rio
Usefulness of synthetic datasets for diatom automatic detection using a deep-learning approach
Engineering Applications of Artificial Intelligence· 2024DOI
Aishwarya Venkataramanan, Pierre Faure-Giovagnoli, Cyril Regan, David Heudre, Cécile Figus, Philippe Usseglio-Polatera, Cédric Pradalier, Martin Laviale
Gaussian Latent Representations for Uncertainty Estimation using Mahalanobis Distance in Deep Classifiers
2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)· 2023DOI
Venkataramanan, Aishwarya; Benbihi, Assia; Laviale, Martin; Pradalier, Cédric
Integrating Visual and Semantic Similarity Using Hierarchies for Image Retrieval
Lecture Notes in Computer Science, Computer Vision Systems· 2023DOI
Aishwarya Venkataramanan, Martin Laviale, Cédric Pradalier
Deliverables (24)
Documents, reports
Documents, reports
Documents, reports
Documents, reports
Documents, reports
Other Results (1)
Periodic Reporting for period 2 - iMagine (Imaging data and services for aquatic science)