| Multi-stage reinforcement learning for object detection J König, S Malberg, M Martens, S Niehaus, A Krohn-Grimberghe, ... Advances in Computer Vision: Proceedings of the 2019 Computer Vision …, 2020 | 23 | 2020 |
| Comparative analysis of machine learning algorithms for multi-syndrome classification of neurodegenerative syndromes L Lampe, S Niehaus, HJ Huppertz, A Merola, J Reinelt, K Mueller, ... Alzheimer's research & therapy 14 (1), 62, 2022 | 17 | 2022 |
| Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging L Lampe, HJ Huppertz, S Anderl-Straub, F Albrecht, T Ballarini, ... NeuroImage: Clinical 37, 103320, 2023 | 16 | 2023 |
| A standardized clinical data harmonization pipeline for scalable ai application deployment (fhir-dhp): Validation and usability study E Williams, M Kienast, E Medawar, J Reinelt, A Merola, SAI Klopfenstein, ... JMIR Medical Informatics 11, e43847, 2023 | 13 | 2023 |
| Domain specific cues improve robustness of deep learning based segmentation of ct volumes M Kloenne, S Niehaus, L Lampe, A Merola, J Reinelt, I Roeder, N Scherf Scientific Reports (Nature Publisher Group), 2020, 2019 | 13 | 2019 |
| A comparative study of semi-and self-supervised semantic segmentation of biomedical microscopy data N Horlava, A Mironenko, S Niehaus, S Wagner, I Roeder, N Scherf arXiv preprint arXiv:2011.08076, 2020 | 6 | 2020 |
| Automatic quality control framework for more reliable integration of machine learning-based image segmentation into medical workflows E Williams, S Niehaus, J Reinelt, A Merola, PG Mihai, K Villringer, ... arXiv preprint arXiv:2112.03277, 2021 | 3 | 2021 |
| Quality control for more reliable integration of deep learning-based image segmentation into medical workflows E Williams, S Niehaus, J Reinelt, A Merola, PG Mihai, I Roeder, N Scherf, ... | 2 | 2021 |
| How to predict relapse in leukemia using time series data: A comparative in silico study H Hoffmann, C Baldow, T Zerjatke, A Gottschalk, S Wagner, E Karg, ... Plos one 16 (11), e0256585, 2021 | 2 | 2021 |
| System and method for the quality assurance of data-based models S Niehaus, M Diebold, J Reinelt, D Lichterfeld US Patent App. 17/788,025, 2023 | 1 | 2023 |
| FHIR-DHP: A Standardized Clinical Data Harmonisation Pipeline for scalable AI application deployment E Williams, M Kienast, E Medawar, J Reinelt, A Merola, ... medRxiv, 2022.11. 07.22281564, 2022 | 1 | 2022 |
| System for the automated harmonisation of structured data from different capture devices S Niehaus, D Lichterfeld, M Diebold, J Reinelt US Patent App. 18/043,418, 2024 | | 2024 |
| Classifier system and method for generating classification models in a distributed manner S Niehaus, M Diebold, D Lichterfeld US Patent App. 17/609,252, 2022 | | 2022 |
| Automated quality monitoring for more reliable integration of neural networks into medical workflows S Niehaus AI. Lounge (Data Science/AI in Lifescience), 2022 | | 2022 |
| MACHINE LEARNING FOR BUILDINGS’ ENERGY CONSUMPTION PREDICTION IN EARLY DESIGN PHASES S Elmers, A Hollberg BauSim Conference Proceedings 9, 2022 | | 2022 |
| Ein Ansatz zur Einführung von Complex Event Processing zum workfloworientierten Software-Monitoring S Niehaus Gesellschaft für Informatik eV, 2016 | | 2016 |
Nico ScherfMax Planck Institute for Human Cognitive and Brain Sciences, Leipzig, GermanyVerified email at tu-dresden.de
