@article {680,
	title = {Deep transformation models for functional outcome prediction after acute ischemic stroke},
	journal = {Biometrical Journal},
	volume = {65},
	year = {2023},
	pages = {2100379},
	author = {Herzog, Lisa and Kook, Lucas and G{\"o}tschi, Andrea and Petermann, Katrin and H{\"a}nsel, Martin and Hamann, Janne and D{\"u}rr, Oliver and Wegener, Susanne and Sick, Beate}
}
@conference {675,
	title = {Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Gaussian Processes Regression Model},
	booktitle = { International Conference on Information Fusion (FUSION)},
	year = {2023},
	pages = {1-8},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Charleston, SC, USA},
	doi = {10.23919/FUSION52260.2023.10224159},
	author = {Patrick Hoher and Johannes Reuter and Daniel Dold and Dennis Griesser and Felix Govaers and Wolfgang Koch}
}
@conference {676,
	title = {Incremental one-class learning using regularized null-space training for industrial defect detection},
	booktitle = {16th International Conference on Machine Vision (ICMV)},
	year = {2023},
	month = {11/2023},
	abstract = {One-class incremental learning is a special case of class-incremental learning, where only a single novel class is incrementally added to an existing classifier instead of multiple classes.
This case is relevant in industrial defect detection scenarios, where novel defects usually appear during operation. 
Existing rolled-out classifiers must be updated incrementally in this scenario with only a few novel examples.
In addition, it is often required that the base classifier must not be altered due to approval and warranty restrictions.
While simple finetuning often gives the best performance across old and new classes, it comes with the drawback of potentially losing performance on the base classes (catastrophic forgetting).
Simple prototype approaches work without changing existing weights and perform very well when the classes are well separated but fail dramatically when not.
In theory, null-space training (NSCL) should retain the basis classifier entirely, as parameter updates are restricted to the null space of the network with respect to existing classes.
However, as we show, this technique promotes overfitting in the case of one-class incremental learning.
In our experiments, we found that unconstrained weight growth in null space is the underlying issue, leading us to propose a regularization term (R-NSCL) that penalizes the magnitude of amplification.
The regularization term is added to the standard classification loss and stabilizes null-space training in the one-class scenario by counteracting overfitting. 
We test the method{\textquoteright}s capabilities on two industrial datasets, namely AITEX and MVTec, and compare the performance to state-of-the-art algorithms for class-incremental learning.},
	author = {Matthias Hermann and Georg Umlauf and Bastian Goldl{\"u}cke and Matthias O.  Franz}
}
@article {682,
	title = {Novel AI-Based Algorithm for the Automated Computation of Coronal Parameters in Adolescent Idiopathic Scoliosis Patients: A Validation Study on 100 Preoperative Full Spine X-Rays},
	journal = {Global Spine Journal},
	year = {2023},
	pages = {21925682231154543},
	author = {Berlin, Clara and Adomeit, Sonja and Grover, Priyanka and Dreischarf, Marcel and Halm, Henry and D{\"u}rr, Oliver and Obid, Peter}
}
@conference {674,
	title = {Visual Pitch and Roll Estimation For Inland Water Vessels},
	booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
	year = {2023},
	pages = {1961-1967},
	publisher = {IEEE},
	organization = {IEEE},
	address = {London, United Kingdom},
	doi = {10.1109/ICRA48891.2023.10160460},
	author = {Dennis Griesser and Georg Umlauf and Matthias O. Franz}
}
@article {683,
	title = {140. Automated measurement technique for coronal parameters using a novel artificial intelligence algorithm: an independent validation study on 100 preoperative AP spine X-rays},
	journal = {The Spine Journal},
	volume = {22},
	year = {2022},
	pages = {S74},
	author = {Berlin, Clara and Adomeit, Sonja and Grover, Priyanka and Dreischarf, Marcel and D{\"u}rr, Oliver and Obid, Peter}
}
@article {670,
	title = {Fast and efficient image novelty detection based on mean-shifts},
	journal = {Sensors | Unusual Behavior Detection Based on Machine Learning },
	year = {2022},
	author = {Matthias Hermann and Georg Umlauf and Bastian Goldl{\"u}cke and Matthias O. Franz}
}
@conference {663,
	title = {Image novelty detection based on mean-shift and typical set size},
	booktitle = {21th International Conference on Image Analysis and Processing, ICIAP},
	year = {2022},
	author = {Matthias Hermann and Bastian Goldl{\"u}cke and Matthias O. Franz}
}
@conference {665,
	title = {Targetless Lidar-camera registration using patch-wise mutual information},
	booktitle = {International Conference on Information Fusion},
	year = {2022},
	author = {Matthias Hermann and Dennis Griesser and Bernhard Gundel and Daniel Dold and Georg Umlauf and Matthias O. Franz}
}
@article {685,
	title = {Validation study of an algorithm based on artificial intelligence for automated computation of coronal parameters on preoperative AP X-rays},
	journal = {Brain and Spine},
	volume = {2},
	year = {2022},
	pages = {101156},
	author = {Adomeit, Sonja and Berlin, Clara and Grover, Priyanka and Dreischarf, Marcel and Halm, Henry and D{\"u}rr, Oliver and Obid, Peter}
}
@conference {629,
	title = {Biologically-inspired vs. CNN texture representations in novelty detection},
	booktitle = {Applications of Machine Learning 2021},
	year = {2021},
	pages = {118430I},
	publisher = {International Society for Optics and Photonics},
	organization = {International Society for Optics and Photonics},
	author = {Michael Grunwald and Matthias Hermann and Freiberg, Fabian and Matthias O. Franz}
}
@proceedings {627,
	title = {CNN-Based Monocular 3D Ship Detection Using Inverse Perspective},
	year = {2020},
	author = {Dennis Griesser and Daniel Dold and Georg Umlauf and Matthias O. Franz}
}
@conference {598,
	title = {Optical Surface Detection: A novelty detection approach based on CNN-encoded features},
	booktitle = {SPIE Optics and Photonics},
	year = {2018},
	month = {10/2018},
	pages = {10752 - 10752 - 13},
	author = {Grunwald, Michael and Matthias Hermann and Freiberg, Fabian and Matthias O. Franz}
}
@conference {509,
	title = {Radiometric calibration of digital cameras using neural networks},
	booktitle = {Optics and Photonics for Information Processing XI},
	year = {2017},
	month = {08/2017},
	publisher = {SPIE - International Society for Optics and Photonics},
	organization = {SPIE - International Society for Optics and Photonics},
	doi = {10.1117/12.2272559},
	url = {http://dx.doi.org/10.1117/12.2272559},
	author = {Michael Grunwald and Pascal Laube and Martin Schall and Georg Umlauf and M O Franz}
}
@conference {503,
	title = {Radiometric calibration of digital cameras using sparse Gaussian processes},
	booktitle = {Workshop Farbbildverarbeitung},
	year = {2016},
	author = {Michael Grunwald and Jens Gansloser and M O Franz}
}
@article {504,
	title = {Wahrnehmungsorientierte optische Inspektion von texturierten Oberfl{\"a}chen},
	journal = {INFORMATIK 2016, Lecture Notes in Informatics (LNI), Gesellschaft f{\"u}r Informatik},
	volume = {259},
	year = {2016},
	pages = {1963{\textendash}1968},
	author = {Michael Grunwald and M O Franz}
}
@conference {485,
	title = {On-line CAD Reconstruction with Accumulated Means of Local Geometric Properties},
	booktitle = {Curves and Surfaces, 8th International Conference, Paris 2014},
	year = {2015},
	pages = {181-201},
	publisher = {Springer},
	organization = {Springer},
	author = {Klaus Denker and Bernd Hamann and Georg Umlauf},
	editor = {Boissonnat, J-D and Cohen, A and Gibaru, O and Gout, C and Lyche, T and Mazure, M-L and Schumaker, L L}
}
@article {489,
	title = {Pixel-wise Hybrid Image Registration on Wood Decors},
	journal = {BW-CAR| SINCOM},
	year = {2015},
	pages = {24},
	isbn = { 978-3-00-051859-1},
	author = {Michael Grunwald and M{\"u}ller, J and Martin Schall and Pascal Laube and Georg Umlauf and M O Franz}
}
@conference {490,
	title = {Radiometric calibration of digital cameras using Gaussian processes},
	booktitle = {SPIE Optics+ Optoelectronics},
	year = {2015},
	publisher = {International Society for Optics and Photonics},
	organization = {International Society for Optics and Photonics},
	doi = {10.1117/12.2178601},
	author = {Martin Schall and Michael Grunwald and Georg Umlauf and M O Franz}
}
@conference {486,
	title = {{Support Vector Machines for Classification of Geometric Primitives in Point Clouds}},
	booktitle = {Curves and Surfaces, 8th International Conference, Paris 2014},
	year = {2015},
	pages = {80-95},
	publisher = {Springer},
	organization = {Springer},
	author = {Manuel Caputo and Klaus Denker and M O Franz and Pascal Laube and Georg Umlauf},
	editor = {Boissonnat, J-D and Cohen, A and Gibaru, O and Gout, C and Lyche, T and Mazure, M-L and Schumaker, L L}
}
@article {216,
	title = {Local energy-optimizing subdivision algorithms},
	journal = {Computer Aided Geometric Design},
	volume = {25},
	year = {2008},
	pages = {137-147},
	author = {Ingo Ginkel and Georg Umlauf}
}
@conference {207,
	title = {Online triangulation of laser-scan data},
	booktitle = {Proceedings of the 17th International Meshing Roundtable 2008},
	year = {2008},
	author = {Klaus Denker and Burkhard Lehner and Georg Umlauf},
	editor = {R.~Garimella}
}
@article {222,
	title = {Symmetry of shape charts},
	journal = {Computer Aided Geometric Design},
	volume = {25},
	year = {2008},
	pages = {131-136},
	author = {Ingo Ginkel and Georg Umlauf}
}
@article {196,
	title = {Analyzing a generalized Loop subdivision scheme},
	journal = {Computing},
	volume = {79},
	year = {2007},
	pages = {353-363},
	author = {Ingo Ginkel and Georg Umlauf}
}
@conference {190,
	title = {Natural neighbor concepts in scattered data interpolation and discrete function approximation},
	booktitle = {GI Lecture Notes in Informatics, Visualization of Large and Unstructured Data Sets},
	year = {2007},
	author = {Tom Bobach and Georg Umlauf},
	editor = {H.~Hagen and M.~Hering-Bertram and C.~Garth}
}
@article {191,
	title = {Normals of subdivision surfaces and their control polyhedra},
	journal = {Computer Aided Geometric Design},
	volume = {24},
	year = {2007},
	pages = {112-116},
	author = {Ingo Ginkel and J{\"o}rg Peters and Georg Umlauf}
}
@conference {212,
	title = {Survey of techniques for data-dependent triangulations},
	booktitle = {GI Lecture Notes in Informatics, Visualization of Large and Unstructured Data Sets},
	year = {2007},
	author = {Burkhard Lehner and Georg Umlauf and Bernd Hamann},
	editor = {H.~Hagen and M.~Hering-Bertram and C.~Garth}
}
@conference {206,
	title = {Tuning subdivision algorithms using constrained energy minimization},
	booktitle = {Mathematics of Surfaces XII},
	year = {2007},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	author = {Ingo Ginkel and Georg Umlauf},
	editor = {R.~Martin and M.~Sabin and J.~Winkler}
}
@conference {184,
	title = {Controlling a subdivision tuning method},
	booktitle = {Curve and Surface Fitting},
	year = {2006},
	author = {Ingo Ginkel and Georg Umlauf},
	editor = {A.~Cohen and J.-L.~Merrien and L.L.~Schumaker}
}
@conference {219,
	title = {Loop subdivision with curvature control},
	booktitle = {Eurographics Symposium on Geometry Processing},
	year = {2006},
	publisher = {Eurographics},
	organization = {Eurographics},
	author = {Ingo Ginkel and Georg Umlauf},
	editor = {K.~Polthier and A.~Sheffer}
}
@conference {215,
	title = {On normals and control nets},
	booktitle = {Mathematics of Surfaces XI},
	year = {2005},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	author = {Ingo Ginkel and J{\"o}rg Peters and Georg Umlauf},
	editor = {R.~Martin and H.~Bez and M.~Sabin pages = 233-239}
}
