Wissenschaftliche Publikationen
2023
T.
Harweg,
M.
Wagner and
F.
Weichert,
"Agent-Based Simulation for Infectious Disease Modelling over a Period of Multiple Days, with Application to an Airport Scenario"
,
International Journal of Environmental Research and Public Health,
vol. 20,
no. 1,
2023.
 Link |
N.
Piatkowski,
K.
Morik,
N.
Kriege,
C.
Morris,
M.
Fey,
F.
Weichert,
N.
Bertram,
J.
Ellert,
J.
Fischer and
L.
Pfahler,
"Structured Data"
in Machine Learning under Resource Constraints - Fundamentals,
De Gruyter,
2023,
pp. 99--178.
 doi:10.1515/9783110785944-004 |
R.
Hergenröder,
F.
Weichert,
K.
Wüstefeld and
V.
Shpacovitch,
"Virus Detection"
in Machine Learning under Resource Constraints - Applications,
De Gruyter,
2023,
pp. 21--42.
| doi:10.1515/9783110785982-010 |
D.
Matuszczyk and
F.
Weichert,
"Reading Direct-Part Marking Data Matrix Code in the Context of Polymer-Based Additive Manufacturing"
,
Sensors,
vol. 23,
no. 3,
2023.
 Datei | 10.3390/s23031619 |
2022
N.
Tschorn,
D.
Matuszczyk and
F.
Weichert,
"Deep Learning based Synthetic Image Generation for Defect Detection in Additive Manufacturing Industrial Environments"
,
International Conference on Mechanical Engineering and Robotics Research,
2022.
C.
Rest,
D.
Fisseler,
F.
Weichert and
G. G. W.
Müller,
"Illumination-based augmentation for cuneiform deep neural sign classification"
,
Journal on Computing and Cultural Heritage (accepted for publication),
2022.
| Link |
J.
Lins,
T.
Harweg,
F.
Weichert and
K.
Wohlgemuth,
"Potential of deep learning methods for deep level particle characterization in crystallization"
,
Applied Sciences (accepted for publication),
2022.
2021
A.
Roth,
K.
Wüstefeld and
F.
Weichert,
"A Data-Centric Augmentation Approach for Disturbed Sensor Image Segmentation"
,
Journal of Imaging,
vol. 7 (10),
2021.
| PDF | https://doi.org/10.3390/jimaging7100206 |
T.
Harweg,
D.
Bachmann and
F.
Weichert,
"Agent-based Simulation of Pedestrian Dynamics for Exposure Time Estimationin Epidemic Risk Assessment"
,
Journal of Public Health,
2021.
| Link | https://doi.org/10.1007/s10389-021-01489-y |
M.
Fey,
J. E.
Lenssen,
F.
Weichert and
J.
Leskovec,
"GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings"
,
International Conference on Machine Learning (ICML),
2021.
| Link |
2020
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 |
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 |
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 |
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+),
2020.
| PDF | Link |
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. 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,
pp. 1-4,
2020.
| PDF | Link | 10.1109/SENSORS47125.2020.9278935 |
M.
Kleineberg,
M.
Fey and
F.
Weichert,
"Adversarial Generation of Continuous Implicit Shape Representations"
in Eurographics,
2020.
| PDF | Link |
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 |
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.