M.Sc. Nick Theisen

Research Associate of the Active Vision Group


My research is focused on hyperspectral image analysis and machine learning in computer vision contexts. This includes semantic segmentation of hyperspectral images using classical methods as well as artificial neural networks.


I offer bachelor and master theses related to the above mentioned topics. If you are interested just get in touch with me.



Memmesheimer, Raphael; Häring, Simon; Theisen, Nick; Paulus, Dietrich (2022): Skeleton-DML: Deep Metric Learning for Skeleton-Based One-Shot Action Recognition. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. IEEE. S. 837--845.

von Gladiss, Anselm; Memmesheimer, Raphael; Theisen, Nick; Bakenecker, Anna C.; Buzug, Thorsten M.; Paulus, Dietrich (2022): Reconstruction of 1D Images with a Neural Network for Magnetic Particle Imaging. In: Bildverarbeitung für die Medizin 2022. Informatik aktuell. Springer Vieweg, Wiesbaden. S. 247--252.

von Gladiss, Anselm; Kramer, Ivanna; Theisen, Nick; Memmesheimer, Raphael; Bakenecker, Anna C.; Buzug, Thorsten M.; Paulus, Dietrich (2022): Data augmentation for training a neural network for image reconstruction in MPI. In: International Workshop on Magnetic Particle Imaging.


Memmesheimer, Raphael; Theisen, Nick; Paulus, Dietrich (2021): SL-DML: Signal Level Deep Metric Learning for Multimodal One-Shot Action Recognition. In: 25th International Conference on Pattern Recognition, {ICPR} 2020, Virtual Event / Milan, Italy, January 10-15, 2021. IEEE. S. 4573-4580.


Memmesheimer, Raphael; Theisen, Nick; Paulus, Dietrich (2020): Gimme Signals: Discriminative signal encoding for multimodal activity recognition. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE.

Memmesheimer, Raphael; Kramer, Ivanna; Seib, Viktor; Theisen, Nick; Paulus, Dietrich (2020): Robotic Imitation by Markerless Visual Observation and Semantic Associations. In: 2020 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE. S. 275--280.


Theisen, Nick; Paulus, Dietrich (2019): Verbessern der temporalen {K}ohärenz in semantisch segmentierten, multispektralen {B}ildsequenzen. In: Püschel, Frank; Stanke, Gerd; Pochanke, Michael: Tagungsband zum 24. Workshop Farbbildverarbeitung. Berlin, Germany: Gesellschaft zur Förderung angewandter Informatik e.V.. Bd. 24. S. 75-85.

Seib, Viktor; Theisen, Nick; Paulus, Dietrich (2019): Boosting 3D Shape Classification with Global Verification and Redundancy-free Codebooks. In: Tremeau, Alain; Farinella, Giovanni Maria; Braz, Jose: Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SciTePress. Bd. 5. S. 257 - 264.


Memmesheimer, Raphael; Wettengel, Niklas Yann; Debald, Lukas; Eckert, Anatoli; Möhlenhof, Thies; Evers, Tobias; Heuer, Gregor; Theisen, Nick; Buchhold, Lukas; Eisenmenger, Jannis; Häring, Simon; Paulus, Dietrich (2018): RoboCup 2018 - homer@UniKoblenz (Germany). Universität Koblenz-Landau, Fachbereich Informatik. Nr. 4/2018. Arbeitsberichte aus dem Fachbereich Informatik.