| An adaptive spatial filter for user-independent single trial detection of event-related potentials H Woehrle, MM Krell, S Straube, SK Kim, EA Kirchner, F Kirchner IEEE Transactions on Biomedical Engineering 62 (7), 1696-1705, 2015 | 71 | 2015 |
| How to evaluate an agent's behavior to infrequent events?—Reliable performance estimation insensitive to class distribution S Straube, MM Krell Frontiers in Computational Neuroscience 8, 43, 2014 | 66 | 2014 |
| Rotational data augmentation for electroencephalographic data MM Krell, SK Kim 2017 39th Annual International Conference of the IEEE Engineering in …, 2017 | 64 | 2017 |
| pySPACE-A Signal Processing and Classification Environment in Python MM Krell, S Straube, A Seeland, H Wöhrle, J Teiwes, JH Metzen, ... Frontiers in Neuroinformatics 7, 40, 2013 | 64 | 2013 |
| On the applicability of brain reading for predictive human-machine interfaces in robotics EA Kirchner, SK Kim, S Straube, A Seeland, H Wöhrle, MM Krell, M Tabie, ... PloS one 8 (12), e81732, 2013 | 52 | 2013 |
| Concept of a data thread based parking space occupancy prediction in a Berlin pilot region T Tiedemann, T Vögele, MM Krell, JH Metzen, F Kirchner AAAI Workshop: AI for Transportation, 2015 | 42 | 2015 |
| Learning coupled dynamic models of underwater vehicles using Support Vector Regression B Wehbe, MM Krell OCEANS 2017-Aberdeen, 1-7, 2017 | 29 | 2017 |
| Data Augmentation for Brain-Computer Interfaces: Analysis on Event-Related Potentials Data MM Krell, A Seeland, SK Kim arXiv preprint arXiv:1801.02730, 2018 | 28 | 2018 |
| Recupera-Reha: Exoskeleton Technology with Integrated Biosignal Analysis for Sensorimotor Rehabilitation EA Kirchner, N Will, M Simnofske, LMV Benitez, B Bongardt, MM Krell, ... 2. Transdisziplinäre Konferenz "Technische Unterstützungssysteme, die die …, 2016 | 26 | 2016 |
| Comparison of sensor selection mechanisms for an ERP-based brain-computer interface D Feess, MM Krell, JH Metzen PloS one 8 (7), e67543, 2013 | 25 | 2013 |
| Efficient Sequence Packing without Cross-contamination: Accelerating Large Language Models without Impacting Performance MM Krell, M Kosec, SP Perez, M Iyer, AW Fitzgibbon | 16 | 2022 |
| Learning magnetic field distortion compensation for robotic systems L Christensen, M Krell, F Kirchner 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 16 | 2017 |
| Classifier transfer with data selection strategies for online support vector machine classification with class imbalance MM Krell, N Wilshusen, A Seeland, SK Kim Journal of Neural Engineering 14 (2), 025003, 2017 | 15 | 2017 |
| Generalizing, Decoding, and Optimizing Support Vector Machine Classification MM Krell http://nbn-resolving.de/urn:nbn:de:gbv:46-00104380-12, 2015 | 14 | 2015 |
| A Capacity Scaling Law for Artificial Neural Networks G Friedland, M Krell arXiv preprint arXiv:1708.06019, 2017 | 12 | 2017 |
| Empirical comparison of distributed source localization methods for single-trial detection of movement preparation A Seeland, MM Krell, S Straube, EA Kirchner Frontiers in human neuroscience 12, 340, 2018 | 11 | 2018 |
| Online model identification for underwater vehicles through incremental support vector regression B Wehbe, A Fabisch, MM Krell 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 11 | 2017 |
| New one-class classifiers based on the origin separation approach MM Krell, H Wöhrle Pattern Recognition Letters, 2015 | 11 | 2015 |
| Balanced Relative Margin Machine—The missing piece between FDA and SVM classification MM Krell, D Feess, S Straube Pattern Recognition Letters 41, 43-52, 2014 | 11 | 2014 |
| Benchmarking the Performance of Accelerators on National Cyberinfrastructure Resources for Artificial Intelligence/Machine Learning Workloads A Nasari, H Le, R Lawrence, Z He, X Yang, M Krell, A Tsyplikhin, ... Practice and Experience in Advanced Research Computing, 1-9, 2022 | 10 | 2022 |
Hendrik WöhrleFachhochschule Dortmund, DFKI Robotics Innovation Centerdfki.de의 이메일 확인됨
