Extraction of spatially confined small-scale waves from high-resolution all-sky airglow images based on machine learning.

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Title: Extraction of spatially confined small-scale waves from high-resolution all-sky airglow images based on machine learning.
Authors: Wüst, Sabine1 (AUTHOR) sabine.wuest@dlr.de, Strutz, Jakob2,3 (AUTHOR), Hannawald, Patrick1 (AUTHOR), Steffen, Jonas4 (AUTHOR), Lienhart, Rainer5 (AUTHOR), Bittner, Michael1,6 (AUTHOR)
Source: Atmospheric Measurement Techniques. 2026, Vol. 19 Issue 10, p3539-3556. 18p.
Database: Academic Search Ultimate
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An: 194401854
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  Data: Extraction of spatially confined small-scale waves from high-resolution all-sky airglow images based on machine learning.
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  Data: <searchLink fieldCode="JN" term="%22Atmospheric+Measurement+Techniques%22">Atmospheric Measurement Techniques</searchLink>. 2026, Vol. 19 Issue 10, p3539-3556. 18p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=194401854
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        Value: 10.5194/amt-19-3539-2026
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      – Code: eng
        Text: English
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        StartPage: 3539
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      – TitleFull: Extraction of spatially confined small-scale waves from high-resolution all-sky airglow images based on machine learning.
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            NameFull: Strutz, Jakob
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            NameFull: Hannawald, Patrick
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            NameFull: Steffen, Jonas
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            NameFull: Lienhart, Rainer
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              Text: 2026
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              Y: 2026
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