[ESIP-all] Call for Abstracts - AGU Fall Meeting
hamed at radiant.earth
Tue Jun 30 12:50:49 EDT 2020
We would like to draw your attention to the following Earth and Space
Science Informatics session at the 2020 Fall AGU Meeting (virtual), 7-11
*Session Title*: Solving Training Data Bottleneck for Artificial
Intelligence/Machine Learning in Earth Science
*Section*: Earth and Space Science Informatics
*Session Viewer Link*:
Manil Maskey/NASA HQ
Hamed Alemohammad/Radiant Earth Foundation
Rahul Ramachandran/NASA MSFC
Subit Chakrabarti/Indigo Agriculture
*Session Description*: While there are successful applications of
Artificial Intelligence/Machine Learning (AI/ML) in Earth Science, the
wider adoption of AI/ML has been limited. The challenge is no longer the
lack of algorithms, tools, or computing resources, but rather the dearth of
training data. Access to training data for supervised learning is required
to attract AI/ML practitioners to tackle Earth Science problems. Creating
labeled data at sufficient scales to support AI/ML algorithms is still a
bottleneck and new strategies to increase training data size and diversity
need to be explored. This session seeks submissions from AI/ML
practitioners and data curators using different approaches or existing
products to create new datasets. This session will enable the practitioners
to share successful approaches to scale the process of generating labeled
datasets. We also seek submissions focusing on best practices for labeling
and structuring data including catalog and standardization to benchmark and
share training data.
Please consider contributing to our discussion on machine learning training
datasets to accelerate the Earth science machine learning.
Please note that the *abstract deadline is Wednesday, 29 July 2020*.
Visit the 2020 Fall AGU website at https://www.agu.org/fall-meeting for the
most up to date information about the virtual meeting. Since this is primarily
a virtual attendance conference, the registration fee will be about half
the normal rate.
We apologize for multiple emails you may receive regarding this session via
multiple mailing lists.
We are looking forward to hearing about your work.
*Hamed Alemohammad, PhD*
Chief Data Scientist
Radiant Earth Foundation
m: (617) 794-3657
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