Scientific Publications - WG "Intelligent Sensing in Computer Graphics"
2025
M.
Schäferhoff,
K.
Peper,
T.
Ambrosat,
C.
Heinze,
D.
Matuszczyk,
F.
Weichert,
B.
Brune,
D.
Ungermann and
M.
Geist,
"13. Symposium Experimentelle Untersuchungen von Baukonstruktionen"
in Schriftenreihe Konstruktiver Ingenieurbau Dresden,
2025.
pp. 40--51.
K.
Wüstefeld and
F.
Weichert,
"Signal model approximation through domain-aware image stream generation"
in Sixth International Conference on Computer Vision and Information Technology (CVIT 2025),
SPIE,
2025.
T.
Haselhoff,
M. D.
Jedrusiak,
F.
Weichert and
S.
Moebus,
"Introducing NORBAERT - an open source software to facilitate the research on complex networks from the acoustic environment",
2025.
2024
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.
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.
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.
A.
Böckenkamp,
"Efficient, collision-free multi-robot navigation in an environment abstraction framework",
Dissertation,
Universität Dortmund,
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.
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.
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.
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.

H.
Müller and
F.
Weichert,
Vorkurs Informatik - Der Einstieg ins Informatikstudium (2023).
....
6
Springer Vieweg,
2023.
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.
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.
J. E.
Lenssen,
"Differentiable algorithms with data-driven parameterization in 3D vision",
Dissertation,
Universität Dortmund,
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.
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.

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.

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.
2020

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.

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.