F. A. Dreger, S. Kuhlmann, F. Weichert and G. Rinkenauer, "4-DOF Robotic Arm Simulator for Machine Operator Training and Performance Evaluation: Engineering Design and Experimental Validation" , International Conference on Applied Human Factors and Ergonomics, 2024.

M. Jedrusiak, T. Harweg, T. Haselhoff, B. T. Lawrence, S. Moebus and F. Weichert, "Towards an interdisciplinary formalization of soundscapes" , Journal of the Acoustical Society of America, vol. 155, no. 4, 2024.

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

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

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.

H. Müller and F. Weichert, Vorkurs Informatik - Der Einstieg ins Informatikstudium (2023). .... 6 Springer Vieweg, 2023.

Link

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

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.

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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.

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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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. 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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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.

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Link

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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Link

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.

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. 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. 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.