SPOC Machine Learning for EO

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Author: InnEO Space
Level: Advanced
Study time: 25 hours
Video time: >5 hours
Exams: 14

Course overview

The course, with video content, intermediate and final tests, ebooks, practical activities and other materials, focuses on Machine Learning and Earth Observation.

Certification included

Successful completion of the course will result in the awarding of the certificate.

What's included?

20 Units
> 5 h Video
Non-evalutative tests and Exams
PDF & ebook
1 Certification
Do you want to develop your career? Go to our dedicated "InnEO PRO" section

Goal

The overall objective of InnEO’Space PhD project is to prepare young researchers for a successful career

Europe

Inneo Space has received funding from the European Union's Horizon 2020-research and innovation programme-under Grant Agreement nº101006275

InnEO Space project

Get more information about the our project

Course Lessons

MEET THE LECTURERS

Our team

Contact our lecturers and staff for more information on the contents of the SPOC. Click on the "+" to learn more and click on the photo to contact them.

Prof. Josiane Mothe

Prof. Josiane Mothe is full professor in computer science since 2002 at the CNRS IRIT lab. She is a specialist in information retrieval, data mining, big data and applied machine learning and teaches these topics mainly at the master level at Université de Toulouse where she is part of the INSPE. She currently leads the InnEO Space PhD project H2020 which gathers together 5 European partners, and she also participates in the UNIVERSEH, Erasmus+ project.

Prof. Mihai Ivanovici

Prof. Mihai Ivanovici is a full professor and is head of MIV Laboratory, within Department of Electronics and Computers, Transilvania University of Brașov, România and member of the IEEE Signal Processing and IEEE Geoscience and Remote Sensing societies. His research interest and expertise are in the field of colour, multispectral and hyperspectral image processing and analysis. Currently he is supervising PhD in the field of electronics, telecommunications and information technologies.

Prof. Fabio Del Frate

Prof. Fabio Del Frate is a Full Professor at the University of Rome “Tor Vergata”, where he teaches courses on Remote Sensing and Applied Electromagnetism. There he is also the Coordinator of the “Design, Application, Regulation of UAVs” Master program and Erasmus coordinator for the Engineering Macroarea. In 2006 Fabio Del Frate co-founded GEO-K srl, the first spin-off company of the University of “Tor Vergata” of which he is now President.

Teaching assistant Davide De Santis

Davide De Santis received the M.Sc. degree in Environmental Engineering (cum laude) from the Tor Vergata University of Rome (TVU) in 2017, where he is currently a PhD candidate in Geoinformation. From 2020 he is co-lecturer of “Image Processing Laboratory” as part of the “Remote Sensing and Cartography” course at TVU. His research interests mainly include optical remote sensing, machine learning and climate change.
Click on the description for more information on his scientific production.

Lecturer Radu Coliban

Radu Coliban is a Lecturer within the Department of Electronics and Computers, Transilvania University of Brașov, where he teaches courses on Image Processing and Computer Architecture. His main research interests are color and hyperspectral image processing and digital electronics design.

Post-Doc Md Zia Ullah

Md Zia Ullah is a Post-doctoral researcher in computer science at IRIT, Université Toulouse Jean Jaures, France. He works on information retrieval and machine learning and information retrieval, and lectures on data analytics at the Université Toulouse Capitole. He received his PhD degree in 2016 from the Toyohashi University of Technology (TUT), Japan. His research areas are Information retrieval, Natural language processing, and applied machine learning. His research has focused on query performance prediction, adaptive information retrieval, search intent mining, deep learning-based histopathology image recognition, and developing tools. He has co-patented an adaptive IR technique and published his research outcomes in the International journals and conferences of his domain, including ACM Transactions on Information Systems (TOIS), ACM Transactions on Intelligent Systems and Technology (TIST), ACM SIGIR Conference on Research and Development in Information Retrieval, CIKM, and IEEE Engineering in Medicine and Biology Society (EMBS).

Teaching assistant Nathalie Neptune

Nathalie Neptune is currently an Associate teacher and researcher at the University of Toulouse, in France. She received her PhD from Université Paul Sabatier, in Toulouse, France, in 2022. During her PhD, she proposed a novel method to annotate satellite images showing changes in forests with words extracted from scientific publications. She was a Schlumberger Foundation Faculty for the Future fellow from 2017 to 2020. Her research interests include multimodal data mining using deep learning approaches for environmental phenomena detection and monitoring. She works at the intersection of computer vision, text mining, information retrieval and remote sensing.

PhD student Lorenzo Giuliano Papale

Lorenzo Giuliano Papale is an Environmental Engineer and a PhD student in

Geoinformation at "Tor Vergata" University of Rome. His main activities are related to SAR Remote sensing

and physics-based Machine Learning algorithms for applications in Atmosphere and Land domains.

Our COMPANIES

Meet our core team

All of our instructors are highly qualified professionals, widely acknowledged in their field.