Semantic Segmentation with Deep Convolutional Neural Networks for Automated Dust Detection in Goes-R Satellite Imagery

Earth and Space Science Open Archive Presented WorkOpen AccessYou are viewing the latest version by default [v1]Semantic Segmentation with Deep Convolutional Neural Networks for Automated Dust Detection in Goes-R Satellite ImageryAuthorsTalhaKhaniDNicholasElmeriDMuthukumaranRamasubramanianEmilyBerndtIkshaGurungAaronKaulfusManilMaskeyiDRahulRamachandranSee all authors Talha KhaniDCorresponding Author• Submitting AuthorNASA Marshall Space Flight CenteriDhttps://orcid.org/0000-0003-3874-4075view email addressThe email was not providedcopy email addressNicholas ElmeriDUniversity of Alabama in HuntsvilleiDhttps://orcid.org/0000-0002-6343-6210view email addressThe email was not providedcopy email addressMuthukumaran RamasubramanianUniversity of Alabama in Huntsvilleview email addressThe email was not providedcopy email addressEmily BerndtNASA Marshall Space Flight Centerview email addressThe email was not providedcopy email addressIksha GurungUniversity of Alabama in Huntsvilleview email addressThe email was not providedcopy email addressAaron KaulfusUniversity of Alabama in Huntsvilleview email addressThe email was not providedcopy email addressManil MaskeyiDUniversity of Alabama in HuntsvilleiDhttps://orcid.org/0000-0002-5087-6903view email addressThe email was not providedcopy email addressRahul RamachandranNASA Marshall Space Flight Centerview email addressThe email was not providedcopy email address