Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Scarlet Stadtler"'
Publikováno v:
Frontiers in Remote Sensing, Vol 5 (2024)
Remote sensing has enabled large-scale crop classification for understanding agricultural ecosystems and estimating production yields. In recent years, machine learning has become increasingly relevant for automated crop classification. However, the
Externí odkaz:
https://doaj.org/article/f013e094a96841428e05bad07a9381f4
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 4, Iss 1, Pp 150-171 (2022)
Air quality is relevant to society because it poses environmental risks to humans and nature. We use explainable machine learning in air quality research by analyzing model predictions in relation to the underlying training data. The data originate f
Externí odkaz:
https://doaj.org/article/6212e8aaa25544bca03c65bff08aa3c1
Autor:
Bing Gong, Michael Langguth, Yan Ji, Amirpasha Mozaffari, Scarlet Stadtler, Karim Mache, Martin G. Schultz
Publikováno v:
Geoscientific model development 15(23), 8931-8956 (2022). doi:10.5194/gmd-15-8931-2022
Geoscientific model development (2022). doi:10.5194/gmd-2021-430
Geoscientific model development (2022). doi:10.5194/gmd-2021-430
Numerical weather prediction (NWP) models solve a system of partial differential equations based on physical laws to forecast the future state of the atmosphere. These models are deployed operationally, but they are computationally very expensive. Re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::08f79941ebbed049b9eadb1711c88826
https://doi.org/10.5194/gmd-2021-430
https://doi.org/10.5194/gmd-2021-430
Autor:
Clara Betancourt, Timo T. Stomberg, Ann-Kathrin Edrich, Ankit Patnala, Martin G. Schultz, Ribana Roscher, Julia Kowalski, Scarlet Stadtler
Publikováno v:
Geoscientific model development discussions (2022). doi:10.5194/gmd-2022-2
Geoscientific model development 15(11), 4331-4354 (2022). doi:10.5194/gmd-15-4331-2022
Geoscientific model development : GMD 15(11), 4331-4354 (2022). doi:10.5194/gmd-15-4331-2022
Geoscientific model development 15(11), 4331-4354 (2022). doi:10.5194/gmd-15-4331-2022
Geoscientific model development : GMD 15(11), 4331-4354 (2022). doi:10.5194/gmd-15-4331-2022
Geoscientific model development : GMD 15(11), 4331-4354 (2022). doi:10.5194/gmd-15-4331-2022
Published by Copernicus, Katlenburg-Lindau
Published by Copernicus, Katlenburg-Lindau
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::73bf73c6131b170fa317d3aaf284ddbc
https://juser.fz-juelich.de/record/905607
https://juser.fz-juelich.de/record/905607
Publikováno v:
Machine Learning and Knowledge Extraction; Volume 4; Issue 1; Pages: 150-171
Machine learning and knowledge extraction 4(1), 150-171 (2022). doi:10.3390/make4010008
Machine learning and knowledge extraction 4(1), 150-171 (2022). doi:10.3390/make4010008
Air quality is relevant to society because it poses environmental risks to humans and nature. We use explainable machine learning in air quality research by analyzing model predictions in relation to the underlying training data. The data originate f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ad35b1e9a0ed70a657c5e628d4577b6
https://mediatum.ub.tum.de/1654676
https://mediatum.ub.tum.de/1654676
Autor:
Stefan Kollet, Markus Abel, Julia Kowalski, Martin G. Schultz, Benedikt Gräler, Scarlet Stadtler, Susanne Crewell, Ribana Roscher
Artificial intelligence (AI) methods currently experience rapid development and are also used more and more frequently in environmental and Earth system sciences. To date however, this is often done in the context of isolated rather than systematic s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4fd3d51fbc3bc82982f71f6b8a0abeeb
https://doi.org/10.5194/egusphere-egu21-211
https://doi.org/10.5194/egusphere-egu21-211
Autor:
Julia Kowalski, Timo Stomberg, Clara Betancourt, Ann-Kathrin Edrich, Martin G. Schultz, Ribana Roscher, Ankit Patnala, Scarlet Stadtler
Publikováno v:
EGU General Assembly 2021, vEGU21, Online, Online, 2021-04-19-2021-04-30
Göttingen : Copernicus Gesellschaft mbH EGU21-7596, 1 Seite (2021). doi:10.5194/egusphere-egu21-7596
Abstracts & presentations / EGU General Assembly 2021
Abstracts & presentations / EGU General Assembly 2021EGU General Assembly 2021, vEGU21, online, 2021-04-19-2021-04-30
Göttingen : Copernicus Gesellschaft mbH EGU21-7596, 1 Seite (2021). doi:10.5194/egusphere-egu21-7596
Abstracts & presentations / EGU General Assembly 2021
Abstracts & presentations / EGU General Assembly 2021EGU General Assembly 2021, vEGU21, online, 2021-04-19-2021-04-30
s & presentations : EGU General Assembly 2021 EGU General Assembly 2021, vEGU21, online, 19 Apr 2021 - 30 Apr 2021; G��ttingen : Copernicus Gesellschaft mbH EGU21-7596, 1 Seite (2021). doi:10.5194/egusphere-egu21-7596
Published by Copernicus
Published by Copernicus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad06d2916cb8ede7a605a0a9ddc45012