News Release

Diving into the world of AI and image processing - a series of workshops organised by the Horizon Europe ANERIS Project

Over 400 participants tuned into the fascinating talks from the field of AI, Deep learning, and Imaging

Meeting Announcement

Pensoft Publishers

Geographic Distribution of Workshop Participants


The three workshops saw attendees from all around the world.

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Credit: Euro-Bioimaging

The Horizon Europe ANERIS project aims to tackle the rapid loss of ocean biodiversity by developing innovative tools and technology for monitoring, research and management of marine life. A large part of ANERIS’s efforts center around imaging technologies applied in the context of marine research - underwater observatories, species recognition imaging software and workflows for analysis of imaging data. The project also gives special attention to knowledge transfer and empowering citizen scientists and early career researchers (ECRs).

The end of November and the first week of December 2023 marked one such activity in ANERIS. The project partners from Euro-Bioimaging, France Bioimaging, and University of Haifa organised a public imaging workshop on “AI Basics for Image Processing” which enjoyed high attendance and a great public response from citizen scientists, students and young researchers.

Set up in three sessions between 29th of November and the 7th of December, the AI-themed workshop enjoyed more than 400 participants from all around the world (see image).

Each of the three sessions was curated thematically and involved speakers from many institutions, including ANERIS participants. 

The first theme “AI Basics for Image Processing” featured insightful talks on “Introduction to image processing” (Jean Yves Tinevez - Institut Pasteur), “AI enhanced microscopy imaging: challenges and perspectives” (Estibaliz Gomez de Mariscal - Instituto Gulbenkian de Ciencia) and “Deep learning and classical machine learning / demo of classification and segmentation” (Thierry Pecot - Rennes University & France Bioimaging) establishing a solid knowledge base on how machine learning and AI can be utilised in the field of imaging.

The second session “Image Restoration” featured in-depth lectures on “Microscopy Image Restoration: Physics-Driven or Data-Driven Models” (Daniel Sage - EPFL), “Denoising microscopy images with self-supervised deep-learning” (Joran Deschamps - Human Technopole), and “Submarine video image restoration” (Tali Treibitz - University of Haifa)” providing more specific information on improving image clarity for analysis, especially related to underwater images.

The final session featured presentations centered around the intriguing topics of “Image Classification and Segmentation”, with talks on “Image segmentation and classification using deep learning” (Perrine Paul-Gilloteaux - CNRS; France Bioimaging), “AI for Marine life classification and Drone images analysis” (Enoc Martinez - the Universitat Politecnica de Catalunya and the iMagine project & Elena Vollmer - the Karlsruher Institute of Technology and the AI4EOSC project), and “Plankton classification using Ecotaxa (Demo)” (Victor Retanauer - Fotonower & Sorbonne University), giving a thorough outline of various techniques for segmentation & classification of different biodiversity imaging data.

The transformative sessions provided a unique opportunity for participants to delve into the complex intersection between AI, deep learning, and imaging, interact with accomplished researchers at the forefront of imaging science, ask questions, and gain insight into the potential future of this field.

For anyone who missed the live workshops, the slides are available in Zenodo, and the recordings are available as a playlist in the  Euro-Bioimaging YouTube channel. 


ANERIS receives funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101094924. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Commission. Neither the EU nor the EC can be held responsible for them.


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