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Geoscientific Instrumentation, Methods and Data Systems An interactive open-access journal of the European Geosciences Union
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GI | Articles | Volume 9, issue 2
Geosci. Instrum. Method. Data Syst., 9, 267–273, 2020
https://doi.org/10.5194/gi-9-267-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Instrum. Method. Data Syst., 9, 267–273, 2020
https://doi.org/10.5194/gi-9-267-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 09 Jul 2020

Research article | 09 Jul 2020

Auroral classification ergonomics and the implications for machine learning

Derek McKay and Andreas Kvammen

Data sets

Replication Data for: Auroral Image Classification with Deep Neural Networks Andreas Kvammen, Kristoffer Wickstrøm, Derek McKay, and Noora Partamies https://doi.org/10.18710/SSA38J

Kiruna All-Sky Camera Urban Brändström http://www2.irf.se/allsky/data.html

Publications Copernicus
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Short summary
Researchers are making increasing use of machine learning to improve accuracy, efficiency and consistency. During such a study of the aurora, it was noted that biases or distortions had crept into the data because of the conditions (or ergonomics) of the human trainers. As using machine-learning techniques in auroral research is relatively new, it is critical that such biases are brought to the attention of the academic and citizen science communities.
Researchers are making increasing use of machine learning to improve accuracy, efficiency and...
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