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Design-KIT - Artificial intelligence in mechanical component development
Design-KIT - Artificial intelligence in mechanical component development © ELISE GmbH Researchers: SörenDittmer, David Erzmann, Henrik Harms Project funding: Bundesministerium für Bildung und Forschung (BMBF)
Section: FB3
Relevance:

100%
Publications
Action, P. Sabatier (Hrsg.), S. 440-446, Springer Verlag, 1990. 2021 Tobias Kluth Gael Rigaud 2020 SörenDittmer On deep learning applied to inverse problems – A chicken-and-egg problem Erstgutachter: Prof. [...] Kernel sizes in convolutional neural networks. Betreuer: Prof. Dr. Dr. h.c. Peter Maaß, Dr. SörenDittmer 28.09.2020 Alexander Denker (Mathematik) Application of Neural Networks For Solving Inverse Problems [...] Journal of Imaging, Inverse Problems and Imaging 7(11), 243 S., 2021. DOI: 10.3390/jimaging7110243 S. Dittmer, T. Kluth, M. Henriksen, P. Maaß. Deep image prior for 3D magnetic particle imaging: A quantitative
Section: FB3
Relevance:

24%
Prof. Dr. Dr. h.c. Peter Maaß
07.01593 S. Dittmer , C. Schönlieb, P. Maaß . Ground Truth Free Denoising by Optimal Transport. Zur Veröffentlichung eingereicht. online unter: https://arxiv.org/abs/2007.01575 S. Dittmer , P. Maaß . A [...] Fractional Kernel sizes in convolutional neural networks Betreuer: Prof. Dr. Dr. h.c. Peter Maaß, SörenDittmer 28.09.2020 Jannik Wildner (Bachelorarbeit Technomathematik) Out of Distribution Detection for [...] periodischen Gebieten Betreuer: Dr. Alexander Konschin, Prof. Dr. Dr. h.c. Peter Maaß 21.09.2017 SörenDittmer (Masterarbeit Mathematik) Mathematical Analysis of Information Loss and Errors in Neural Networks
Section: FB3
Relevance:

23%

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