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Image Labeler: A Web Interface to Catalog Earth Science EventsAdvances in machine learning (ML) have made it possible to automatically detect Earth science phenomena from satellite imagery. While useful, ML algorithms typically require an extensive dataset containing labeled images for training. Systematic labeling and management of such datasets is quite cumbersome. With this in mind, we present the Image Labeler. Image Labeler is a fast and scalable cloud-based tool that facilitates the rapid development of Earth science event databases, in order to aid automated ML-based image classification.





Document ID
20190030777
Acquisition Source
Marshall Space Flight Center
Document Type
Poster
Authors
Acharya, Ashish
(Alabama Univ. Huntsville, AL, United States)
Freitag, Brian
(Alabama Univ. Huntsville, AL, United States)
Gurung, Iksha
(Alabama Univ. Huntsville, AL, United States)
Maskey, Manil
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Ramachandran, Rahul
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Date Acquired
September 12, 2019
Publication Date
September 7, 2019
Subject Category
Documentation And Information Science
Report/Patent Number
MSFC-E-DAA-TN72827
Report Number: MSFC-E-DAA-TN72827
Meeting Information
Meeting: National Weather Association Annual Meeting
Location: Huntsville, AL
Country: United States
Start Date: September 7, 2019
End Date: September 12, 2019
Sponsors: National Weather Association
Funding Number(s)
CONTRACT_GRANT: NNM11AA01A
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
Case Study
Decision Support Service
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