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Welcome to the MACLEAN website.

Introduction:

MACLEAN (Machine learning for Earth Observation) is an action within the GDR MADICS (BigData, Data Science) http://www.madics.fr/, started in January 2019. We organise regularly workshops, seminars, tutorials, young researcher days at national and international levels to promote scientifique exchanges and discussions from both Earth Observation and machine learning communities.

Aims and Scopes:

The huge amount of data currently produced by modern Earth Observation (EO) missions has raised up new challenges for the Remote Sensing communities. EO sensors are now able to offer (very) high spatial resolution images with revisit time frequencies never achieved before considering different kind of signals, e.g., multi-(hyper)spectral optical, radar, LiDAR and Digital Surface Models.

In this context, modern machine learning techniques can play a crucial role to deal with such amount of heterogeneous, multi-scale and multi-modal data. Some examples of techniques that are gaining attention in this domain include deep learning, domain adaptation, semi-supervised approach, time series analysis and active learning. Even though the use of machine learning and the development of ad-hoc techniques are gaining increasing popularity in the EO domain, we can witness that a significant lack of interaction between domain experts and machine learning researchers still exists.

The main goal of MACLEAN is to provide an active forum where machine learning researchers and domain-experts can meet each other, in order to exchange, debate and draw short and long term research objectives around the exploitation and analysis of EO data via Machine Learning techniques.

Chairs:

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