Scientific Publications - WG "Intelligent Sensing in Computer Graphics"
2022
J. E.
Lenssen,
"Differentiable algorithms with data-driven parameterization in 3D vision",
Dissertation,
Universität Dortmund,
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
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 |
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 |
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 |
2019
A.
Toma,
J.
Wenner,
J. E.
Lenssen and
J.
Chen,
"Adaptive Quality Optimization of Computer Vision Tasks in Resource-Constrained Devices using Edge Computing"
in 2019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID),
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.
 File |
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.
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.
| File |
2018
M.
Fey,
J. E.
Lenssen,
F.
Weichert and
H.
Müller,
"SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels"
in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR),
2018.
pp. 869-877.
| File |
A.
Toma,
A.
Starinow,
J. E.
Lenssen and
J.
Chen,
"Saving Energy for Cloud Applications in Mobile Devices using Nearby Resources"
in 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP),
2018.
J. E.
Lenssen,
A.
Toma,
A.
Seebold,
V.
Shpacovitch,
P.
Libuschewski,
F.
Weichert,
J.
Chen and
R.
Hergenröder,
"Real-Time Low SNR Signal Processing for Nanoparticle Analysis with Deep Neural Networks"
,
11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018),
vol. 4 (BIOSIGNALS),
pp. 36-47,
2018.
J. E.
Lenssen,
M.
Fey and
P.
Libuschewski,
"Group Equivariant Capsule Networks"
in Neural Information Processing Systems (NIPS) 32,
2018.
| File |
2017
J. E.
Lenssen,
V.
Shpacovitch,
D.
Siedhoff,
P.
Libuschewski,
R.
Hergenröder and
F.
Weichert,
"A Review of Nano-Particle Analysis with the PAMONO-Sensor"
,
Biosensors: Advances and Reviews, IFSA Publishing,
pp. 81-100,
2017.
V.
Shpacovitch,
I.
Sidorenko,
J. E.
Lenssen,
V.
Temchura,
F.
Weichert,
H.
Müller,
K.
Überla,
A.
Zybin,
A.
Schramm and
R.
Hergenröder,
"Application of the PAMONO-sensor for Quantification of Microvesicles and Determination of Nano-particle Size Distribution"
,
Sensors,
vol. 17,
pp. 1-14,
2017.
| 10.3390/s17020244 |
J. E.
Lenssen,
V.
Shpacovitch and
F.
Weichert,
"Real-time Virus Size Classification using Surface Plasmon Resonance and Convolutional Neural Networks"
,
Bildverarbeitung für die Medizin 2017,
pp. 98-103,
2017.
2015
S.
Skibinski,
J. H.
Terhorst,
F.
Weichert and
H.
Müller,
"Large-Scale Fusion of Collective, Areal Vehicle Data"
,
IEEE International Conference on Multisensor Fusion and Integration,
pp. 152-159,
2015.
2008
H.
Müller,
D.
Biermann,
P.
Kersting,
T.
Michelitsch,
C.
Begau,
C.
Heuel,
R.
Joliet,
J.
Kolanski,
M.
Kröller,
C.
Moritz,
D.
Niggemann,
M.
Stöber,
T.
Stönner,
J.
Varwig and
D.
Zhai,
"Intuitive Visualization and Interactive Analysis of Pareto Sets Applied On Production Engineering Systems"
in Success in Evolutionary Computation, Springer-Verlag, Berlin,
Springer-Verlag,
2008,
pp. 189-214.
2000
A.
Hinkenjann,
"Effiziente Lösungsverfahren für Sichtbarkeitsprobleme in der realitätsnahen Bildsynthese",
Dissertation,
TU Dortmund, Lehrstuhl Informatik VII,
2000.
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