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Part 1 will focus on the use of Doodler (h … Part 1 will focus on the use of Doodler (https://github.com/Doodleverse/dash_doodler), a 'human-in-the-loop' labeling tool for image segmentation (described in this paper: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021EA002085). We'll cover the two primary uses of Doodler; a) for relatively rapid image segmentation of a small set of images, and b) for making libraries of labeled imagery for training Machine Learning models to automate the process of image segmentation on larger datasets. We'd ideally like participants to label the same imagery in-class so we can discuss image interpretation and label agreement. This may even result in a publishable dataset; participants would receive co-authorship and could opt-in/out.</br></br>We will provide example datasets and models, but participants will also be encouraged to bring their own imagery sets. That way, participants will have time to familiarize themselves with the burgeoning Doodleverse tools (https://github.com/Doodleverse) in between classes on their own data.rse) in between classes on their own data. +
Pre_Webinar_Preparations.pdf +
United States +
dbuscombe@gmail.com +
CSDMS 2022 Webinars +
USGS/Marda Science +
University of North Carolina, Greensboro +
Buscombe +
Goldstein +
Webinar +
NO STATE +
North Carolina +
Machine Learning - Part 1 +
10:00:00, 10 November 2022 +
REGISTRATION NOW CLOSED +
BarGUQ5CuA0 +
United States +
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17:35:58, 13 September 2022 +
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22:34:06, 11 June 2025 +
Marine Working Group +, Terrestrial Working Group +, Coastal Working Group +, Education and Knowledge Transfer (EKT) Working Group +, Cyberinformatics and Numerics Working Group +, Hydrology 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 + and River Network Modeling Initiative +
