Wissenschaftliche Publikationen

2020

M. D. Jedrusiak and F. Weichert, "A Deep Learning Approach for Denoising Air-Coupled Ultrasonic Responds Data" , International Journal of Artificial Intelligence and Applications (IJAIA), vol. 11, no. 4, pp. 15-28, 2020.
 PDF Link
K. Wüstefeld and F. Weichert, "An Automated Rapid Test for Viral Nanoparticles Based on Spatiotemporal Deep Learning" , IEEE Sensors (accepted for publication), 2020.
T. Harweg, A. Peter, D. Bachmann and F. Weichert, CNN-Based Deep Architecture for Health Monitoring of Civil and Industrial Structures using UAVs: 6th International Electronic Conference on Sensors and Applications.
 PDF https://doi.org/10.3390/ecsa-6-06640
M. Fey, J. E. Lenssen, C. Morris, J. Masci and N. Kriege, "Deep Graph Matching Consensus" in International Conference on Learning Representations (ICLR), 2020.
 PDF Link
J. E. Lenssen, C. Osendorfer and J. Masci, "Deep Iterative Surface Normal Estimation" in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
 PDF Link
R. Chabra, J. E. Lenssen, E. Ilg, T. Schmidt, J. Straub, S. Lovegrove and R. Newcombe, "Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstruction" in European Conference on Computer Vision (ECCV), 2020.
 Link
M. Fey, J. Yuen and F. Weichert, "Hierarchical Inter-Message Passing for Learning on Molecular Graphs" in ICML Graph Representation Learning and Beyond (GRL+) (accepted for publication), 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
M. Kleineberg, M. Fey and F. Weichert, "Adversarial Generation of Continuous Implicit Shape Representations" in Eurographics (accepted for publication), 2020.
 PDF Link

2019

M. Fey, "Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks" in ICLR Workshop on Representation Learning on Graphs and Manifolds, 2019.
 Datei
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
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.
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
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.
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.
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
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.

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
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
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.
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
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