Description: This workshop will be a hands on introduction on general Machine Learning methods for Image Segmentation for planetary applications. In this segment, we will tackle the problem of detecting mound like features in DTMs from the Mars Arabia terra. Mounds are positive relief like features which may contain evidence of water sources beneath them. Automatically detecting or segmenting them holds great utility. We will achieve this by training Autoencoder based models directly on elevation models, to learn appropriate representations that preserve the most relevant features, rendering them useful for downstream tasks. Techniques such as these are transferable to other input types such as RGB images, and thus serve as ground work for this line of applications.
Europlanet 2024 RI has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871149.
Conveners:
Sahib Julka,Ute Amerstorfer
Mon, 19 Sep, 10:00–11:30 (CEST)|Room Splinter Sala de Prensa
Please use the buttons below to download the presentation materials or to visit the external website where the presentation is linked. Regarding the external link, please note that Copernicus Meetings cannot accept any liability for the content and the website you will visit.
You are going to open an external link to the asset as indicated by the session. Copernicus Meetings cannot accept any liability for the content and the website you will visit.