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Artificial Intelligence for Earth Monitoring MOOC

Artificial Intelligence for Earth Monitoring MOOC

EUMETSAT, ECMWF, Mercator Ocean International and the EEA have jointly developed a new massive open online course (MOOC) on Artificial Intelligence (AI) and Earth monitoring, and we are proud to be part of this project!

Artificial intelligence and machine learning (ML) are undoubtedly becoming more and more present in our daily lives, proving important contributions to different fields, like farming, healthcare, and finance, to name a few. In a fast-changing and critical time for Earth Observation (EO), especially for those involved in its use for climate and meteorology, there is huge potential for AI and ML.

This new MOOC starting October 18 offers you a comprehensive overview of the Copernicus Programme and the wealth of EO data it provides, as well as how AI and ML are transforming the interpretation of EO data.

As well as video content, in this MOOC there is also a strong hands-on element with the inclusion of a series of specially-developed Jupyter notebooks that will guide people through the process of working with Copernicus data and new and exciting machine learning algorithms. 

The notebooks are put together using Python and give examples of the different types of Copernicus data (ocean, atmosphere, land and climate) and machine learning algorithms.

To make it easier to follow the notebooks, they are accompanied by dedicated video tutorials that have been produced to explain the content of the notebooks. 

Registration is now open!

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Mail: ai4eo@tum.de
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International AI Future Lab on Artificial Intelligence for Earth Observation @TU_Muenchen @DLR_de, @BMBF_bund funded

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Retweet on TwitterInternational AI Future Lab on AI4EO Retweeted
AvatarXiaoxiang ZHU@xiaoxiang_zhu·
20 May

We are looking for one PostDoc and one PhD student working on #UncertaintyQuantification in #DeepNeuralNetworks for #EarthObservation and their impact on use cases related to #ClimateScience #SeaLevelBudget
Here an overview paper as background info: https://arxiv.org/abs/2107.03342

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Retweet on TwitterInternational AI Future Lab on AI4EO Retweeted
AvatarXiaoxiang ZHU@xiaoxiang_zhu·
18 May

Interested in semantic segmentation, but has no annotation?
Check our recent paper @Zhu_XLab @ai4eo_de led by @sudipansaha published in @IEEE_GRSS #TGRS: 10.1109/TGRS.2022.3174651
code (coming soon): https://gitlab.lrz.de/ai4eo/cd/-/tree/main/unsupContrastiveSemanticSeg
#AI4EO

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Retweet on TwitterInternational AI Future Lab on AI4EO Retweeted
AvatarXiaoxiang ZHU@xiaoxiang_zhu·
18 May

Interested in land use dynamics on the Earth's surface? Check our #DynamicEarthNet dataset -- daily, multi-spectral satellite observations of 75 AOIs across the globe with imagery from #Planetscope and #Sentinels, paired with high quality #LULC labels #AI4EO #CVPR

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