machine learning to identify clouds on NASA satellite images
Organisatsiooni nimi
Scaling and Intelligence Lab (SaIL)
Kokkuvõte
Clouds polluted by anthropogenic aerosols, i.e. microscopic solid and liquid air pollution
particles, at anthropogenic aerosol point sources (Fig 1) help to better understand
anthropogenic impacts on Earth’s climate (Toll et al., 2019). However, visual/manual
identification of polluted cloud tracks is time-consuming. Machine learning has been used to
identify clouds polluted by shipping emissions (Yuan et al., 2019; Yuan et al., 2022;
Watson-Parris et al., 2022)
particles, at anthropogenic aerosol point sources (Fig 1) help to better understand
anthropogenic impacts on Earth’s climate (Toll et al., 2019). However, visual/manual
identification of polluted cloud tracks is time-consuming. Machine learning has been used to
identify clouds polluted by shipping emissions (Yuan et al., 2019; Yuan et al., 2022;
Watson-Parris et al., 2022)
Lõputöö kaitsmise aasta
2023-2024
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KALLOL ROY, Velle Toll, Piia Post
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eesti keel, inglise keel
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Bakalaureus, Magister
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+37256051480
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