Scientific Publications - WG "Intelligent Sensing in Computer Graphics"

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.
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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

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.
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2020

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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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.
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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.
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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.
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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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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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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
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.
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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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2019

M. Fey, "Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks" in ICLR Workshop on Representation Learning on Graphs and Manifolds, 2019.
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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.
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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
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.
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.
M. Fey and J. E. Lenssen, "Fast Graph Representation Learning with PyTorch Geometric" in ICLR Workshop on Representation Learning on Graphs and Manifolds, 2019.
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S. Skibinski, "Extraction, localization, and fusion of collective vehicle data", Dissertation, Universität Dortmund, 2019.
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D. Fisseler, "Contributions to computer-aided analysis of cuneiform tablet fragments", Dissertation, Universität Dortmund, 2019.
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