Zobrazeno 1 - 10
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pro vyhledávání: '"Schröder, Simon"'
Autor:
Alexander Schröder, Simon, Costantini, Ilaria, Etxebarria, Idoia, Manuel Madariaga, Juan, Arana, Gorka
Publikováno v:
In Microchemical Journal September 2024 204
Autor:
Schmarje, Lars, Brünger, Johannes, Santarossa, Monty, Schröder, Simon-Martin, Kiko, Rainer, Koch, Reinhard
Publikováno v:
Sensors 2021, 21(19), 6661
Deep learning has been successfully applied to many classification problems including underwater challenges. However, a long-standing issue with deep learning is the need for large and consistently labeled datasets. Although current approaches in sem
Externí odkaz:
http://arxiv.org/abs/2110.06630
Autor:
Schmarje, Lars, Santarossa, Monty, Schröder, Simon-Martin, Zelenka, Claudius, Kiko, Rainer, Stracke, Jenny, Volkmann, Nina, Koch, Reinhard
Publikováno v:
Proceedings of the European Conference on Computer Vision (ECCV 2022)
Consistently high data quality is essential for the development of novel loss functions and architectures in the field of deep learning. The existence of such data and labels is usually presumed, while acquiring high-quality datasets is still a major
Externí odkaz:
http://arxiv.org/abs/2106.16209
Autor:
Schmarje, Lars, Brünger, Johannes, Santarossa, Monty, Schröder, Simon-Martin, Kiko, Rainer, Koch, Reinhard
A long-standing issue with deep learning is the need for large and consistently labeled datasets. Although the current research in semi-supervised learning can decrease the required amount of annotated data by a factor of 10 or even more, this line o
Externí odkaz:
http://arxiv.org/abs/2012.01768
Publikováno v:
In Molecular Catalysis 15 January 2024 553
In this work, we present MorphoCluster, a software tool for data-driven, fast and accurate annotation of large image data sets. While already having surpassed the annotation rate of human experts, volume and complexity of marine data will continue to
Externí odkaz:
http://arxiv.org/abs/2005.01595
Publikováno v:
IEEE Access 2021
While deep learning strategies achieve outstanding results in computer vision tasks, one issue remains: The current strategies rely heavily on a huge amount of labeled data. In many real-world problems, it is not feasible to create such an amount of
Externí odkaz:
http://arxiv.org/abs/2002.08721
Akademický článek
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Autor:
Schröder, Simon1 (AUTHOR), Richter, Anja1 (AUTHOR), Veith, Talitha1 (AUTHOR), Emanuel, Jackson1 (AUTHOR), Gudermann, Luca1 (AUTHOR), Friedmann, Kirstin1 (AUTHOR), Jeworowski, Lara M.1 (AUTHOR), Mühlemann, Barbara1 (AUTHOR), Jones, Terry C.1,2 (AUTHOR), Müller, Marcel A.1 (AUTHOR), Corman, Victor M.1 (AUTHOR), Drosten, Christian1 (AUTHOR) christian.drosten@charite.de
Publikováno v:
Virology Journal. 11/8/2023, Vol. 20 Issue 1, p1-13. 13p.