%0 Journal Article %1 Marcolongo_Vladymyrov_Lienert_Peleg_Haug_Zscheischler_2022 %A Marcolongo, Aris %A Vladymyrov, Mykhailo %A Lienert, Sebastian %A Peleg, Nadav %A Haug, Sigve %A Zscheischler, Jakob %D 2022 %J Environmental Data Science %K Convolutional Predicting data gross low primary production weather zno networks neural %P e2 %R 10.1017/eds.2022.1 %T Predicting years with extremely low gross primary production from daily weather data using Convolutional Neural Networks %V 1

@article{Marcolongo_Vladymyrov_Lienert_Peleg_Haug_Zscheischler_2022, added-at = {2024-12-11T14:43:20.000+0100}, author = {Marcolongo, Aris and Vladymyrov, Mykhailo and Lienert, Sebastian and Peleg, Nadav and Haug, Sigve and Zscheischler, Jakob}, biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/23c61aa998c054ff440a7ac0c5760414c/scadsfct}, doi = {10.1017/eds.2022.1}, interhash = {6188f8f2b1638d6dafc92918ae4c5637}, intrahash = {3c61aa998c054ff440a7ac0c5760414c}, journal = {Environmental Data Science}, keywords = {Convolutional Predicting data gross low primary production weather zno networks neural}, pages = {e2}, timestamp = {2025-07-29T10:50:32.000+0200}, title = {Predicting years with extremely low gross primary production from daily weather data using Convolutional Neural Networks}, volume = 1, year = 2022 }