Wissenschaftliche Publikationen - AG "Intelligente Sensorik"

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.
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A. Böckenkamp, "Efficient, collision-free multi-robot navigation in an environment abstraction framework", Dissertation, Universität Dortmund, 2023.
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K. Wüstefeld, R. Ebbinghaus and F. Weichert, "Learning to Segment Blob-like Objects by Image-Level Counting" , Applied Sciences, vol. 13, no. 22, 2023.
 Datei 10.3390/app132212219
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
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
N. Sharar, K. Wüstefeld, R. M. Talukder, J. Skolnik, K. Kaufmann, B. Giebel, F. Börger, C. Watzl, F. Weichert, R. Hergenröder and V. Shpacovitch, "The employment of the surface plasmon resonance (SPR) microscopy sensor for the detection of individual extracellular vesicles and non-biological nanoparticles" , Biosensors, vol. 13, no. 4, 2023.
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
H. Müller and F. Weichert, Vorkurs Informatik - Der Einstieg ins Informatikstudium (2023). .... 6 Springer Vieweg, 2023.
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T. Ambrosat, F. Gierschner, A. Hundrup, T. Harweg, F. Weichert, D. Ungermann and W. Flügge, "Automatisierte Inspektion von stahlbaulichen Strukturen mittels Drohne im Innenbereich" , zfv, vol. 5, 2023.
 10.12902/zfv-0441-2023

2022

M. Gaspar, "Bahnplanung mittels impliziter Methoden für spanende und beschichtende Fertigungsverfahren", Dissertation, Universität Dortmund, 2022.
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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.
J. E. Lenssen, "Differentiable algorithms with data-driven parameterization in 3D vision", Dissertation, Universität Dortmund, 2022.
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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.
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M. Fey, "On the power of message passing for learning on graph-structured data", Dissertation, Universität Dortmund, 2022.
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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

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.
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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
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

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.
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M. Kleineberg, M. Fey and F. Weichert, "Adversarial Generation of Continuous Implicit Shape Representations" in Eurographics, 2020.
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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
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.
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J. E. Lenssen, C. Osendorfer and J. Masci, "Deep Iterative Surface Normal Estimation" in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
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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.
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