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|Working group member=Terrestrial Working Group, Coastal Working Group, Marine Working Group, Education and Knowledge Transfer (EKT) Working Group, Cyberinformatics and Numerics Working Group, Hydrology Focus Research Group, Carbonates and Biogenics Focus Research Group, Chesapeake Focus Research Group, Critical Zone Focus Research Group, Human Dimensions Focus Research Group, Geodynamics Focus Research Group, Ecosystem Dynamics Focus Research Group, Coastal Vulnerability Initiative, Continental Margin Initiative, Artificial Intelligence & Machine Learning Initiative, Modeling Platform Interoperability Initiative, River Network Modeling Initiative | |Working group member=Terrestrial Working Group, Coastal Working Group, Marine Working Group, Education and Knowledge Transfer (EKT) Working Group, Cyberinformatics and Numerics Working Group, Hydrology Focus Research Group, Carbonates and Biogenics Focus Research Group, Chesapeake Focus Research Group, Critical Zone Focus Research Group, Human Dimensions Focus Research Group, Geodynamics Focus Research Group, Ecosystem Dynamics Focus Research Group, Coastal Vulnerability Initiative, Continental Margin Initiative, Artificial Intelligence & Machine Learning Initiative, Modeling Platform Interoperability Initiative, River Network Modeling Initiative | ||
|CSDMS meeting presentation=AI%26Seafloor_CSDMS_Clinic_CJJ_May2021_v2.pdf | |||
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Revision as of 19:04, 26 May 2021
CSDMS 2021: Changing Landscapes and Seascapes: Modeling for Discovery, Decision Making, and Communication
Training Datasets for Modeling with AI across the Deep-Ocean Seafloor
Abstract
As agreed at earlier CSDMS forums, the major
impediment in using AI for modeling the deep-ocean seafloor is a lack of training data, the data which guides the AI - whichever set of algorithms is chosen. This clinic will expose participants to globally-extensive datasets which are available through CSDMS. It will debate the scientific questions of why certain data work well, are appropriate to the processes, and are properly scaled.
Participants are encouraged to bring their own AI challenges to the clinic.
Please acknowledge the original contributors when you are using this material. If there are any copyright issues, please let us know (CSDMSweb@colorado.edu) and we will respond as soon as possible.
Of interest for:
