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Stefan Sandfeld
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2020 – today
- 2024
- [j2]Kishan Govind
, Daniela Oliveros, Antonin Dlouhy, Marc Legros
Deep learning of crystalline defects from TEM images: a solution for the problem of 'never enough training data'. Mach. Learn. Sci. Technol. 5(1): 15006 (2024) - [c5]Bashir Kazimi, Karina Ruzaeva, Stefan Sandfeld:
Self-Supervised Learning with Generative Adversarial Networks for Electron Microscopy. CVPR Workshops 2024: 71-81 - [c4]Said Fathalla, Gerrit Günther, Leon Steinmeier, Christine Lemster, Dorothee Kottmeier, Lakxmi Sivapatham, Pier Luigi Buttigieg, Volker Hofmann, Stefan Sandfeld:
The Helmholtz Digitization Ontology: Representing Digital Assets in the Helmholtz Digital Ecosystem. SEMANTiCS (Posters, Demos, Workshops & Tutorials) 2024 - [i13]Ahmad Zainul Ihsan, Said Fathalla, Stefan Sandfeld:
DISO: A Domain Ontology for Modeling Dislocations in Crystalline Materials. CoRR abs/2401.02540 (2024) - [i12]Binh Duong Nguyen, Johannes Steiner, Peter Wellmann, Stefan Sandfeld:
Combining unsupervised and supervised learning in microscopy enables defect analysis of a full 4H-SiC wafer. CoRR abs/2402.13353 (2024) - [i11]Bashir Kazimi, Karina Ruzaeva, Stefan Sandfeld:
Self-Supervised Learning in Electron Microscopy: Towards a Foundation Model for Advanced Image Analysis. CoRR abs/2402.18286 (2024) - 2023
- [c3]Harald Sack
Knowledge Graph Based RDM Solutions NFDI4Culture - NFDI-MatWerk - NFDI4DataScience. CoRDI 2023 - [c2]Ahmad Zainul Ihsan
DISO: A Domain Ontology for Modeling Dislocations in Crystalline Materials. SAC 2023: 1746-1753 - [i10]Kishan Govind, Daniela Oliveros, Antonin Dlouhy, Marc Legros, Stefan Sandfeld:
Deep Learning of Crystalline Defects from TEM images: A Solution for the Problem of "Never Enough Training Data". CoRR abs/2307.06322 (2023) - [i9]Binh Duong Nguyen, Pavlo Potapenko, Aytekin Dermici, Kishan Govind, Stefan Sandfeld:
Efficient Surrogate Models for Materials Science Simulations: Machine Learning-based Prediction of Microstructure Properties. CoRR abs/2309.00305 (2023) - [i8]Karina Ruzaeva, Kishan Govind, Marc Legros, Stefan Sandfeld:
Instance Segmentation of Dislocations in TEM Images. CoRR abs/2309.03499 (2023) - [i7]Chen Zhang, Clémence Bos, Stefan Sandfeld, Ruth Schwaiger:
Unsupervised Learning of Nanoindentation Data to Infer Microstructural Details of Complex Materials. CoRR abs/2309.06613 (2023) - [i6]Ahmad Zainul Ihsan, Said Fathalla, Stefan Sandfeld:
Modeling Dislocation Dynamics Data Using Semantic Web Technologies. CoRR abs/2309.06930 (2023) - [i5]Sébastien Bompas, Stefan Sandfeld:
A Generative Model for Accelerated Inverse Modelling Using a Novel Embedding for Continuous Variables. CoRR abs/2311.11343 (2023) - [i4]Lukas Morand, Tarek Iraki, Johannes Dornheim, Stefan Sandfeld, Norbert Link, Dirk Helm:
Machine learning for structure-guided materials and process design. CoRR abs/2312.14552 (2023) - 2022
- [i3]Aruna Prakash
Automated analysis of continuum fields from atomistic simulations using statistical machine learning. CoRR abs/2206.08048 (2022) - 2021
- [j1]Prince Henry Serrao
OptiMic: A tool to generate optimized polycrystalline microstructures for materials simulations. SoftwareX 15: 100708 (2021) - [c1]Reetu Joseph, Aditya Chauhan, Catriona Eschke, Ahmad Zainul Ihsan, Mehrdad Jalali, Ute Jäntsch, Nicole Jung, C. N. Shyam Kumar, Christian Kübel, Christian Lucas, Matthias Mail, Andrey Mazilkin, Charlotte Neidiger, Mirco Panighel, Stefan Sandfeld, Rainer Stotzka, Richard Thelen, Rossella Aversa:
Metadata Schema to support FAIR Data in Scanning Electron Microscopy. DAMDID/RCDL (Supplementary Proceedings) 2021: 265-277 - [i2]Prince Henry Serrao, Stefan Sandfeld, Aruna Prakash:
OptiMic: A tool to generate optimized polycrystalline microstructures for materials simulations. CoRR abs/2107.02460 (2021) - [i1]M. Vimal, Stefan Sandfeld, A. Prakash:
Grain segmentation in atomistic simulations using orientation-based iterative self-organizing data analysis. CoRR abs/2112.03348 (2021)
Coauthor Index
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