Wissenschaftliche Publikationen - AG "Intelligente Sensorik"

2020

M. Fey, J. Yuen and F. Weichert, "Hierarchical Inter-Message Passing for Learning on Molecular Graphs" in ICML Graph Representation Learning and Beyond (GRL+), 2020.
 PDF Link
Y. Zhao, T. Birdal, J. E. Lenssen, E. Menegatti, L. Guibas and F. Tombari, "Quaternion Equivariant Capsule Networks for 3D Point Clouds" in European Conference on Computer Vision (ECCV), 2020.
 Link
A. Böckenkamp, "roslaunch2: Versatile, Flexible and Dynamic Launch Configurations for the Robot Operating System" in Robot Operating System (ROS): The Complete Reference,Koubaa, Anis, Eds. Heidelberg: Springer International Publishing, 2020, pp. 165--181.
 Link

2019

W. Tillmann, C. Schaak, J. Zajaczkowski, H. Müller, D. Hegels, M. Gaspar, B. Kuhlenkötter and D. D. Störkle, "Investigation of a procedure for the simulation-based optimisation of robot paths for thermal spraying" , Thermal Spray Bulletin, vol. 12, pp. 89-97, 2019.
C. Morris, M. Ritzert, M. Fey, W. L. Hamilton, J. E. Lenssen, G. Rattan and M. Grohe, "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks" in 33rd AAAI Conference on Artificial Intelligence (AAAI-19), 2019.
 Datei
M. Yayla, A. Toma, J. E. Lenssen, J. Chen, F. Weichert and K. Chen, "Resource-efficient Nanoparticle Classification Using Frequency Domain Analysis" , Bildverarbeitung für die Medizin, pp. 339-344, 2019.
M. Yayla, A. Toma, K. Chen, J. E. Lenssen, V. Shpacovitch, R. Hergenröder, F. Weichert and J. Chen, "Nanoparticle Classification Using Frequency Domain Analysis on Resource-Limited Platforms" , Sensors, Special Issue Surface Plasmon Resonance (SPR)-Based Sensors and Their Biological Applications, vol. 19, pp. 1-15, 2019.
 doi.org/10.3390/s19194138
M. Fey, "Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks" in ICLR Workshop on Representation Learning on Graphs and Manifolds, 2019.
 Datei
G. Rinkenauer, T. Plewan, D. Bachmann and F. Weichert, "Vergleich von virtuellen Interaktionssystemen mit einer realen Situation" , Arbeit interdisziplinär analysieren - bewerten - gestalten: 65. Kongress der Gesellschaft für Arbeitswissenschaft, vol. 6, pp. 1-6, 2019.
E. Rusakov, K. Brandenbusch, D. Fisseler, T. Somel, G. A. Fink, F. Weichert and G. Müller, "Generating Cuneiform Signs with Cycle-Consistent Adversarial Networks" , International Workshop on Historical Document Imaging and Processing (HIP19) , pp. 19-24, 2019.
J. Deuse, L. Stankiewicz, R. Zwinkau and F. Weichert, "Automatic generation of methods-time measurement analyses for assembly tasks from motion capture data using convolutional neuronal networks - A proof of concept" , Advances in Human Factors and Systems Interaction (AHFE 2019), Advances in Intelligent Systems and Computing, vol. 959, pp. 141-150, 2019.
A. Toma, J. Wenner, J. E. Lenssen and J. Chen, "Adaptive Quality Optimization of Computer Vision Tasks in Resource-Constrained Devices using Edge Computing" in 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 2019.
M. Fey and J. E. Lenssen, "Fast Graph Representation Learning with PyTorch Geometric" in ICLR Workshop on Representation Learning on Graphs and Manifolds, 2019.
 Datei
D. Fisseler, "Contributions to computer-aided analysis of cuneiform tablet fragments", Dissertation, Universität Dortmund, 2019.
 Link
S. Skibinski, "Extraction, localization, and fusion of collective vehicle data", Dissertation, Universität Dortmund, 2019.
 Link

2018

J. E. Lenssen, M. Fey and P. Libuschewski, "Group Equivariant Capsule Networks" in Neural Information Processing Systems (NIPS) 32, 2018.
 Datei
D. Stoller, I. Vatolkin and H. Müller, "Intuitive and efficient computer aided music rearrangement with optimised processing of audio transitions" , Journal of New Music Research (accepted for publication), 2018.
W. Tillmann, C. Schaak, J. Zajaczkowski, H. Müller, D. Hegels, M. Gaspar, B. Kuhlenkötter and D. D. Störkle, "Investigation into the properties of HVOF-sprayed WC-Co coatings on plane and complex surfaces, manufactured with an evolution-based path planning method" , Thermal Spray Bulletin, vol. 11, 2018.
J. E. Lenssen, A. Toma, A. Seebold, V. Shpacovitch, P. Libuschewski, F. Weichert, J. Chen and R. Hergenröder, "Real-Time Low SNR Signal Processing for Nanoparticle Analysis with Deep Neural Networks" , 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018), vol. 4 (BIOSIGNALS), pp. 36-47, 2018.
N. Kriege, M. Fey, D. Fisseler, P. Mutzel and F. Weichert, "Recognizing Cuneiform Signs Using Graph Based Methods" in International Workshop on Cost-Sensitive Learning (COST), 2018.
 Datei
D. Bachmann, F. Weichert and G. Rinkenauer, "Review of three-dimensional Human-Computer Interaction with Focus on the Leap Motion Controller" , Sensors, vol. 18, pp. 1-39, 2018.
 10.3390/s18072194
A. Toma, A. Starinow, J. E. Lenssen and J. Chen, "Saving Energy for Cloud Applications in Mobile Devices using Nearby Resources" in 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), 2018.
M. Fey, J. E. Lenssen, F. Weichert and H. Müller, "SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels" in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. pp. 869-877.
 Datei
D. Bachmann, F. Bökler, J. Kopec, K. Popp, B. Schwarze and F. Weichert, "Multi-Objective Optimisation based Planning of Power-Line Grid Expansions" , ISPRS International Journal of Geo-Information, vol. 7, pp. 1-22, 2018.
 10.3390/ijgi7070258

2017

J. E. Lenssen, V. Shpacovitch and F. Weichert, "Real-time Virus Size Classification using Surface Plasmon Resonance and Convolutional Neural Networks" , Bildverarbeitung für die Medizin 2017, pp. 98-103, 2017.