First webinar: “Satellite Remote Sensing for Maritime Surveillance”

**First webinar: “*Satellite Remote Sensing for Maritime Surveillance***” 

This webinar was organised within the framework of the EU-funded project AXOLOTL (GA 101158669).

Overview

Satellite data provide complementary capabilities for observing ocean and maritime activity. In this session, we focus on two pressing research fronts: the lack of open ship datasets across spatial resolutions, and the challenge of detecting small vessels in remote sensing imagery.

Topics Covered
The Data Gap in (Small) Ship Detection
Public satellite datasets remain insufficient for training and evaluating robust ship detectors across spatial resolutions. This talk will address:
• An annotated Sentinel-2 subset built using AIS data and visual models to enable open research.
• The challenges of publishing commercial imagery and a mitigation path through a synthetic data generator.

Small Object Detection in Remote Sensing
Detecting ships is already challenging – detecting small ships (e.g., fishing vessels, yachts) is even more difficult due to scale, clutter, and resolution limits. This presentation will focus on:
• The use of late-upsampling instead of early-upsampling for improved efficiency.
• Knowledge distillation between early and late-upsampling networks to enhance small-object detection.

Speakers

Topic 1 — Dr. Andreas Hadjisoteriou, Assistant Scientist at the Cyprus Marine and Maritime Institute (CMMI).
Topic 2 — Dr. Abdelbadie Belmouhcine, Assistant Professor (temporary position) in Computer Science at the Université de Bretagne Sud (UBS).

Moderator

The session was moderated by Professor Minh-Tan Pham, Associate Professor in Computer Science at the Université de Bretagne Sud (UBS) and partner of the AXOLOTL project.

Meet Our Speakers and Moderator

Speakers

Dr. Andreas Hadjisoteriou, Assistant Scientist at the CMMI – Cyprus Marine and Maritime Institute is a results-driven data scientist with a strong engineering background, specializing in computer vision and machine learning. Dr. Hadjisoteriou, through his current position at the CMMI – Cyprus Marine and Maritime Institute, he develops innovative remote sensing solutions, including super-resolution and object detection models for satellite imagery. He holds a PhD in Mechanical Engineering from the University of Sheffield, where his Rolls-Royce-funded research advanced aerospace engineering, and an MEng in Aerospace Engineering with First Class Honours. His expertise spans applied research, advanced data science methodologies, and cross-sector collaboration with academic, research, and industry partners.

Dr. Abdelbadie Belmouhcine, Assistant Professor in Computer Science at the Université Bretagne Sud (UBS) received his PhD in Computer Science from Mohammed V University of Rabat, Morocco, in 2017, where his research focused on contextual information integration for web page classification. Since 2019, he has shifted his research toward image processing and deep learning, beginning with a research internship at the National Conservatory of Arts and Crafts (CNAM), Paris. From 2020 to 2023, he held a postdoctoral position at IFREMER, contributing to both seasons of the Game of Trawls project, which aimed at designing intelligent fishing trawls. In 2023, he joined the University Institute of Technology of Vannes and the IRISA Laboratory as an Assistant Professor (temporary position, ATER in France) in Computer Science, where he has been involved in the AXOLOTL project, focusing on small object detection from satellite imagery. His current research interests include object detection and tracking using deep neural networks.

Moderator

Professor Minh-Tan Pham, Associate Professor in Computer Science at the Université de Bretagne Sud (UBS) received his MSc and PhD degrees from Telecom Bretagne (France) in 2013 and 2016, respectively. He was a Master intern in Laval University (Canada) in 2013. From 2016 to 2019, he was a post-doctoral researcher at the IRISA laboratory (France) and also an invited researcher at TU Berlin (Germany), University of Trento (Italy) and Imperial College London (UK) in 2018. Since 2019, he is an Associate Professor (Habilitation to Supervise Research (HDR) in 2025) at Université Bretagne Sud (France). He is the Head of the Data/AI track of the Bachelor of Computer Sciences at IUT Vannes. His research focuses on computer vision and deep learning applied to remote sensing for Earth observation. Professor Pham is a co-chair of the MACLEAN (Machine learning for earth observation) workshop at ECMLPKDD (7 editions since 2019). He is a Guest Editor of the two journals: Remote Sensing and Machine Learning (Springer), as well as a member of the Editorial Board of Digital Signal Processing (Elsevier). Since 2021, Dr. Pham has been a PI or Co-PI of several research projects of AI/Deep learning applied to remote sensing data at regional, national and European scales.

Webinar Details

Date & Time: 30 September 2025, 10:00 CET
Format: Online via Microsoft Teams

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