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The AI-CORE Project - Artificial Intelligence for Cold Regions

Baumhoer, Celia and Dietz, Andreas and Heidler, Konrad and Zhu, Xiao Xiang and Scheinert, Mirko and Loebel, Erik and Nitze, Ingmar and Christmann, Julia and Humbert, Angelika and Dinter, Tilman and Frickenhaus, Stephan (2022) The AI-CORE Project - Artificial Intelligence for Cold Regions. Data Science Symposium No. 7, 2022-06-27 - 2022-06-28, Geesthacht.

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Official URL: https://hcdc.hereon.de/datahub/static/media/filer_public/99/4c/994c7797-a2e6-438a-86de-fc5758434e0d/data_science_symposium_7_program_abstracts.pdf

Abstract

Funded by the Helmholtz Foundation, the aim of the Artificial Intelligence for COld REgions (AI-CORE) project is to develop methods of Artificial Intelligence for solving some of the most challenging questions in cryosphere research by the example of four use cases. These use cases are of high relevance in the context of climate change but very difficult to tackle with common image processing techniques. Therefore, different AI-based imaging techniques are applied on the diverse, extensive, and inhomogeneous input data sets. In a collaborative approach, the German Aerospace Center, the Alfred-Wegener-Institute, and the Technical University of Dresden work together to address not only the methodology of how to solve these questions, but also how to implement procedures for data integration on the infrastructures of the partners. Within the individual Helmholtz centers already existing competences in data science, AI implementation, and processing infrastructures exist but are decentralized and distributed among the individual centers. Therefore, AI-CORE aims at bringing these experts together to jointly work on developing state of the art tools to analyze and quantify processes currently occurring in the cryosphere. The presentation will give a brief overview of the geoscientific use cases and then address the different challenges that emerged so far in this still on-going project. Moreover, we will give an overview of the status of this implementation and demonstrate the already available functionalities.

Item URL in elib:https://elib.dlr.de/187152/
Document Type:Conference or Workshop Item (Speech)
Title:The AI-CORE Project - Artificial Intelligence for Cold Regions
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Baumhoer, CeliaUNSPECIFIEDhttps://orcid.org/0000-0003-1339-2288UNSPECIFIED
Dietz, AndreasUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Heidler, KonradUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Zhu, Xiao XiangUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Scheinert, MirkoTU DresdenUNSPECIFIEDUNSPECIFIED
Loebel, ErikUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Nitze, IngmarUNSPECIFIEDhttps://orcid.org/0000-0002-1165-6852UNSPECIFIED
Christmann, JuliaAlfred-Wegener-InstitutUNSPECIFIEDUNSPECIFIED
Humbert, AngelikaAlfred Wegener Institute for Polar and Marine Research, Bremerhaven, GermanyUNSPECIFIEDUNSPECIFIED
Dinter, TilmanAlfred-Wegener-InstitutUNSPECIFIEDUNSPECIFIED
Frickenhaus, StephanAlfred-Wegener-InstitutUNSPECIFIEDUNSPECIFIED
Date:June 2022
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:AI, cold regions, deep learning, glaciers, permafrost
Event Title:Data Science Symposium No. 7
Event Location:Geesthacht
Event Type:national Conference
Event Start Date:27 June 2022
Event End Date:28 June 2022
Organizer:Helmholtz/Hereon
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Artificial Intelligence, R - Remote Sensing and Geo Research
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface Dynamics
Remote Sensing Technology Institute > EO Data Science
Deposited By: Baumhoer, Dr. Celia
Deposited On:27 Jul 2022 09:25
Last Modified:24 Apr 2024 20:48

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