Staff

October 2026: MPISuperRes-PnP, a super-resolution method for magnetic particle imaging, has been published in Physics in Medicine & Biology. The code is freely available.

8 July 2026: 2nd Main-Danube Workshop on Computer Vision, Machine Learning and Applications at THWS in Schweinfurt

12 May 2026: Talk “Machine Learning and Model-Based Reconstruction in Magnetic Particle Imaging” at Campus Ignaz Schön

15 January 2026: Vladyslav Gapyak received his doctorate summa cum laude. Thesis title: “Robust and Efficient Algorithms for Image Reconstruction with Applications to Magnetic Particle Imaging”

Courses in the winter semester 2026/27

• Mathematics Bachelor of Mechanical Engineering I

Lab
Lab for Algorithms for Computer Vision, Imaging and Data Analysis

Bachelor’s and master’s theses
I supervise theses in

• computer vision
• machine learning
• imaging and inverse problems, for example magnetic particle imaging
• data analysis

If you are interested, please get in touch by email.

All publications, sorted by year. Citation counts and full texts are available on Google Scholar.

2026

• V. Gapyak, T. März, A. Weinmann. MPISuperRes-PnP: A super-resolution zero-shot plug-and-play reconstruction algorithm for magnetic particle imaging. Physics in Medicine & Biology, 71(19):195033, 2026
• T. Selig, P. Bauer, T. März, M. Storath, J. Frikel, A. Weinmann. Filter-free two-stage reconstruction for low-dose CT across regular and irregular sparse-angle sampling. Sensing and Imaging, 27(1):152, 2026
• T. R. Lenhard, A. Weinmann, T. Koch. Performance optimization of YOLO-FEDER FusionNet for robust drone detection in visually complex environments. Machine Vision and Applications, 37(6):138, 2026
• Y. Ali, J. Müller, A. Weinmann, J. Gregori. Performance of federated versus centralized learning for mammography classification across film–digital domain shift. Frontiers in Digital Health, 8:1715858, 2026
•  M. Dorscht, M. Stark, N. Oberndorfer, B. Böhm, A. Weinmann, A. Dreizler et al. Atomic composition analysis of iron-based particles via single-shot LIBS and spectral fitting under fluctuating plasma conditions. Measurement Science and Technology, 37(4):045501, 2026
• M. Dorscht, N. Oberndorfer, M. Stark, B. Böhm, A. Weinmann, A. Dreizler et al. Optically accessible electrodynamic levitator for in-situ LIBS characterization of iron particles under reactive conditions. Optics Express, 34(6):9652–9668, 2026
• K. Koschnick, A. M. Ferris, M. Stark, D. Stark, J. Welzenbach, N. Winkler, A. Weinmann, C. Hess, B. J. M. Etzold, A. Drochner, T. Franken, D. Geyer, A. Dreizler. Gas-phase Raman spectroscopy for two-dimensional temperature and concentration profiling in the catalytic oxidative dehydrogenation of ethanol. Applied Catalysis A: General, 712:120767, 2026
• T. März, V. Gapyak, A. Weinmann. Higher order regularization using harmonic eigenfunctions for model-based reconstruction in magnetic particle imaging. Inverse Problems, 42(2):025002, 2026
• S. Bianchi, C. Jordan, M. Beukes, E. Hergenröther, T. März, A. Weinmann. Vision-language based object detection for wildlife camera trap data. Third Workshop on Computer Vision for Ecology (CV4E), 2026
• B. Isselmann, Y. Ali, A. Weinmann, J. Gregori. Modality-embedded set transformer pooling for multimodal prostate cancer survival prediction. IEEE CBMS 2026
•  Y. Ali, J. Müller, A. Weinmann, J. Gregori. Explainable and fair federated learning with XGBoost for predicting pathological complete response in breast cancer using multicenter DCE-MRI data. Medical Imaging 2026: Computer-Aided Diagnosis, Proc. SPIE 13926, 192–198, 2026
• T. Selig, L. Groznov, T. März, M. Storath, A. Weinmann. Fine-tuning Gaussian denoisers for fluorescence microscopy image enhancement. Proc. SPIE, 2026
• V. Gapyak, T. März, A. Weinmann. Noise estimation in zero-shot plug-and-play reconstruction for 3D MPI data. Engineering Proceedings, 150(1):92, 2026
• T. Selig, T. März, M. Storath, A. Weinmann. Fine-tuning a denoiser for low-dose CT image reconstruction. Engineering Proceedings, 150(1):38, 2026
• A. Srinivasan, X. Cheng, J. Yi, A. Geng, D. Ivanova, A. Weinmann et al. Hybrid quantum–classical AI for industrial defect classification in welding images. Engineering Proceedings, 150(1):96, 2026
• T. März, V. Gapyak, A. Weinmann. MPI reconstruction using harmonic eigenfunctions. AIP Conference Proceedings, 3489(1):280060, 2026
•  V. Polushko, D. Hatic, R. Rösch, T. März, M. Rauhut, A. Weinmann. Remote sensing imagery for flood detection: exploration of augmentation strategies. AIP Conference Proceedings, 3489(1):120001, 2026
• V. Gapyak, T. März, A. Weinmann. Towards addressing nanoparticle relaxation in model-based reconstruction. International Journal on Magnetic Particle Imaging, 12(1, Suppl. 1):2603021, 2026
• T. R. Lenhard, A. Weinmann, T. Koch. Beyond clear skies: synthetic seasonal and weather variations for real-world drone detection. arXiv:2608.16191, 2026
•  P. Bauer, M. Schwinning, M. Siegel, A. Weinmann, H. Snoussi. Adapting a foundation model for lunar surface height estimation. arXiv:2609.02448, 2026
• D. Ruppel, H. Kutlu, K. A. Neumann, M. Knuth, P. Santos, A. Weinmann et al. Beyond reprojection error: camera calibration with 3D targets. arXiv:2608.05066, 2026
• J. M. Stürmer, J. Knack, T. Koch, A. Weinmann. Simulation code generation for fluid systems using large language models: benchmarking models and prompting strategies. arXiv:2607.29389, 2026
• V. Polushko, T. Bucher, R. Rösch, T. März, M. Rauhut, A. Weinmann. Flood mapping from RGB imagery using a vision foundation model. arXiv:2606.24120, 2026
• A. M. Pangeva, Y. Ferhi, A. Geng, A. Weinmann, D. Ivanova, A. Moghiseh. Schmidt decomposition-based methods for efficient quantum image encoding. arXiv:2606.10874, 2026
• B. Isselmann, D. Göksu, H. Neumann, A. Weinmann. Using deep learning models pretrained by self-supervised learning for protein localization. arXiv:2604.10970, 2026
• V. Gapyak, T. März, A. Weinmann. Debye relaxation in model-based multi-dimensional magnetic particle imaging. arXiv:2603.11708, 2026
• B. Isselmann, D. Göksu, A. Weinmann. Generalization of self-supervised vision transformers for protein localization across microscopy domains. arXiv:2602.05527, 2026
• P. Bauer, M. Schwinning, F. Renk, A. Weinmann, H. Snoussi. Vision-language model for accurate crater detection. arXiv:2601.07795, 2026
• T. R. Lenhard, A. Weinmann, H. Snoussi, T. Koch. Detector-augmented SAMURAI for long-duration drone tracking. arXiv:2601.04798, 2026

2025

• J. Moske, H. Kutlu, P. Groenewold, P. Santos, A. Weinmann, A. Kuijper et al. Photometric stereo for tool wear monitoring: addressing challenges of specular surfaces in sheet metal forming. Manufacturing Review, 12:29, 2025
•  V. Gapyak, T. März, A. Weinmann. Fast trajectory-independent model-based reconstruction algorithm for multi-dimensional magnetic particle imaging. Physics in Medicine & Biology, 70(23):235028, 2025
• V. Gapyak, T. März, A. Weinmann. Reconstruction formulae for 3D field-free line magnetic particle imaging. SIAM Journal on Applied Mathematics, 85(4):1643–1666, 2025
• K. Koschnick, A. M. Ferris, B. Zhang, J. Lill, M. Stark, A. Weinmann, H. H. Limbach, T. Gutmann, D. Geyer, A. Dreizler. High-sensitivity gas-phase Raman spectroscopy for time-resolved in situ analysis of isotope scrambling over platinum nanocatalysts. Analytical Chemistry, 97:18117–18125, 2025
• V. Gapyak, C. E. Rentschler, T. März, A. Weinmann. An ℓ1-plug-and-play approach for MPI using a zero shot denoiser with evaluation on the 3D open MPI dataset. Physics in Medicine & Biology, 70(2):025028, 2025
• S. Volz, M. Storath, A. Weinmann. Degrees-of-freedom penalized piecewise regression. Information and Inference: A Journal of the IMA, 14(1):iaaf002, 2025
• V. Suessle, M. Heurich, C. T. Downs, A. Weinmann, E. Hergenröther. CNN-based flank predictor for quadruped animal species. IET Computer Vision, 19(1), 2025
• T. R. Lenhard, A. Weinmann, K. Franke, T. Koch. SynDroneVision: A synthetic dataset for image-based drone detection. WACV 2025, 7637–7647
• P. Gruner, M. Beukes, V. Suessle, M. Biber, M. Jansen, E. Hergenröther, A. Weinmann. Fine-grained visual classification of antelope species. IbPRIA 2025, 325–339
• T. Selig, P. Bauer, J. Frikel, T. März, M. Storath, A. Weinmann. Two-stage approach for low-dose and sparse-angle CT reconstruction using backprojection. Bildverarbeitung für die Medizin (BVM) 2025, 286–291
• V. Polushko, D. Hatic, R. Rösch, T. März, M. Rauhut, A. Weinmann. Flooded road detection using deep learning and street map semantics for humanitarian aid support. IGARSS 2025
• V. Polushko, T. Bucher, D. Hatic, R. Rösch, T. März, M. Rauhut, A. Weinmann. NeuenahrFlood dataset and an improved human-in-the-loop strategy for efficient flood water segmentation. Earth Resources and Environmental Remote Sensing/GIS Applications XVI, Proc. SPIE 13671, 2025
• P. Bauer, M. Schwinning, F. Renk, A. Weinmann, H. Snoussi. Small lunar crater detection using a few-shot object detection approach with Vision Transformer. 6th International Conference on Computer Vision and Information Technology (CVIT), 2025
• C. Weber, J. Seeger, B. Isselmann, J. Gregori, A. Weinmann. Investigation of domain specific pretraining of a Swin transformer to improve Alzheimer’s disease classification on three different brain imaging modalities. Medical Imaging 2025: Computer-Aided Diagnosis, Proc. SPIE 13407, 484–492, 2025
• B. Isselmann, C. Weber, J. Seeger, A. M. Wink, H. J. M. M. Mutsaerts et al. Investigation of multimodal deep-learning architectures for the classification of Alzheimer’s disease and amyloid status. Medical Imaging 2025: Computer-Aided Diagnosis, Proc. SPIE 13407, 279–286, 2025
• T. R. Lenhard, A. Weinmann, S. Jäger, E. Brucherseifer. Deploying a feedback loop-based training strategy for deep learning-based drone detection. AIP Conference Proceedings, 3182(1):060004, 2025
• V. Gapyak, T. März, A. Weinmann. Model-based reconstruction of 2D distributions from 1D multi-patch data in magnetic particle imaging. AIP Conference Proceedings, 3182(1):090010, 2025
• V. Gapyak, T. März, A. Weinmann. Methods for multi-patching in 3D field-free line magnetic particle imaging. AIP Conference Proceedings, 3315(1):310002, 2025
•  J. Moske, H. Kutlu, A. Steinmeier, P. Groenewold, P. Santos, A. Kuijper et al. Inline wear detection in high-speed progressive dies using photometric stereo. MATEC Web of Conferences, 408:01031, 2025
• H. Kutlu, F. Brucker, B. Kallendrusch, K. A. Neumann, M. E. Schneider et al. Autonomous image-based scanning pipeline for 3D digitization of transparent objects using scene representation in the cultural heritage domain. International Workshop on Spatial Intelligence for Cultural Heritage, 2025

2024

• M. Storath, A. Weinmann. Smoothing splines for discontinuous signals. Journal of Computational and Graphical Statistics, 33(2):651–664, 2024
• V. Gapyak, T. März, A. Weinmann. Variational model-based reconstruction techniques for multi-patch data in magnetic particle imaging. Journal of Computational and Applied Mathematics, 451:116046, 2024
•  V. Polushko, A. Jenal, J. Bongartz, I. Weber, D. Hatic, R. Rösch, T. März, M. Rauhut, A. Weinmann. BlessemFlood21: A high-resolution georeferenced dataset for advanced analysis of river flood scenarios. IEEE Access, 12:176389–176405, 2024
• K. Koschnick, A. M. Ferris, J. Lill, M. Stark, N. Winkler, A. Weinmann, A. Dreizler, D. Geyer. Dual-track spectrometer design for 1D gas-phase Raman spectroscopy. Optics Express, 32(14):24384–24405, 2024
• J. Lill, M. Stark, R. Schultheis, A. Weinmann, A. Dreizler, D. Geyer. Towards non-intrusive, quantitative N2O Raman measurements in ammonia flames. Proceedings of the Combustion Institute, 40(1–4):105458, 2024
• T. R. Lenhard, A. Weinmann, S. Jäger, T. Koch. YOLO-FEDER FusionNet: A novel deep learning architecture for drone detection. ICIP 2024, 2299–2305
• V. Polushko, A. Jenal, J. Bongartz, I. Weber, D. Hatic, R. Rösch, T. März, M. Rauhut, A. Weinmann. BlessemFlood21: Advancing flood analysis with a high-resolution georeferenced dataset for humanitarian aid support. IGARSS 2024
• R. Horst, D. Hagens, E. Hergenröther, A. Weinmann. Real time state detection of a foosball game using CNN-based computer vision. Science and Information Conference (SAI) 2024, 343–354
• C. Weber, J. Seeger, B. Isselmann, M. Günther, A. Weinmann, J. Gregori. Application of Swin Transformer for Alzheimer’s disease classification on structural MRI and FDG-PET brain scans using ADNI data. 2024
• T. März, V. Gapyak, A. Weinmann. A flexible model-based regularized reconstruction approach for magnetic particle imaging. AIP Conference Proceedings, 3094(1):440001, 2024
• V. Gapyak, T. März, A. Weinmann. Quality-enhancing techniques for a two-stage model-based approach for magnetic particle imaging. AIP Conference Proceedings, 3094(1):440002, 2024
• M. Storath, A. Weinmann. Solving higher-order Mumford-Shah models. AIP Conference Proceedings, 3094(1):440006, 2024
• V. Gapyak, C. Rentschler, T. März, A. Weinmann. A zero-shot L1-plug-and-play approach for system-matrix-based MPI. International Journal on Magnetic Particle Imaging, 10(1, Suppl. 1), 2024
• M. Doell, D. Kuehn, V. Suessle, M. J. Burnett, C. T. Downs, A. Weinmann et al. Automated bioacoustic monitoring for South African bird species on unlabeled data. arXiv:2406.13579, 2024
• D. Hagens, J. M. Knaup, E. Hergenröther, A. Weinmann. CNN-based game state detection for a foosball table. arXiv:2404.05357, 2024

2023

• T. R. Dieter, A. Weinmann, S. Jäger, E. Brucherseifer. Quantifying the simulation–reality gap for deep learning-based drone detection. Electronics, 12(10):2197, 2023
• V. Suessle, M. Arandjelovic, A. K. Kalan, A. Agbor, C. Boesch, G. Brazzola, T. Deschner, P. Dieguez, A.-C. Granjon, H. Kuehl, A. Landsmann, J. Lapuente, N. Maldonado, A. Meier, Z. Rockaiova, E. G. Wessling, R. M. Wittig, C. T. Downs, A. Weinmann, E. Hergenröther. Automatic individual identification of patterned solitary species based on unlabeled video data. Journal of WSCG, 31(1–2):1–10, 2023
• T. Dieter, A. Weinmann, E. Brucherseifer. Generating synthetic data for deep learning-based drone detection. AIP Conference Proceedings, 2939(1):030007, 2023
• T. März, V. Gapyak, A. Weinmann. A two-stage model-based regularized reconstruction approach for magnetic particle imaging. AIP Conference Proceedings, 2939(1):100008, 2023

2022 

• V. Gapyak, T. März, A. Weinmann. Quality-enhancing techniques for model-based reconstruction in magnetic particle imaging. Mathematics, 10(18):3278, 2022
•  K. Dieter, K. Koschnick, J. Lill, G. Magnotti, A. Weinmann, A. Dreizler, D. Geyer. Development of a Raman spectrometer for the characterization of gaseous hydrocarbons at high temperatures. Journal of Quantitative Spectroscopy and Radiative Transfer, 277:107978, 2022
•  C. Schmidt, P. Fuchs, A. Weinmann. Object identification on CT data via 3D optical character recognition. International Conference on NDE 4.0, 2022

2021

• U. Reif, A. Weinmann. Clothoid fitting and geometric Hermite subdivision. Advances in Computational Mathematics, 47(4):50, 2021
• L. Kiefer, M. Storath, A. Weinmann. Iterative Potts minimization for the recovery of signals with discontinuities from indirect measurements: the multivariate case. Foundations of Computational Mathematics, 21(3):649–694, 2021
• L. Kiefer, S. Petra, M. Storath, A. Weinmann. Multi-channel Potts-based reconstruction for multi-spectral computed tomography. Inverse Problems, 37(4):045004, 2021
• M. Storath, A. Weinmann. Variational regularization of inverse problems for manifold-valued data. Information and Inference: A Journal of the IMA, 10:195–230, 2021

2020

• L. Kiefer, M. Storath, A. Weinmann. PALMS image partitioning – a new parallel algorithm for the piecewise affine-linear Mumford-Shah model. Image Processing On Line, 10:124–149, 2020
• L. Kiefer, M. Storath, A. Weinmann. An algorithm for second order Mumford-Shah models based on a Taylor jet formulation. SIAM Journal on Imaging Sciences, 13(4):2307–2360, 2020
• M. Storath, A. Weinmann. Wavelet sparse regularization for manifold-valued data. Multiscale Modeling and Simulation, 18(2):674–706, 2020
• L. Kiefer, M. Storath, A. Weinmann. An efficient algorithm for the piecewise affine-linear Mumford-Shah model based on a Taylor jet splitting. IEEE Transactions on Image Processing, 29:921–933, 2020
• P. Grohs, M. Holler, A. Weinmann (eds.). Handbook of Variational Methods for Nonlinear Geometric Data. Springer Nature, 2020
• M. Holler, A. Weinmann. Non-smooth variational regularization for processing manifold-valued data. In: Handbook of Variational Methods for Nonlinear Geometric Data, 51–93, 2020
• M. Baust, A. Weinmann. Manifold-valued data in medical imaging applications. In: Handbook of Variational Methods for Nonlinear Geometric Data, 613–647, 2020

2019

• M. Storath, L. Kiefer, A. Weinmann. Smoothing for signals with discontinuities using higher order Mumford-Shah models. Numerische Mathematik, 143(2):423–460, 2019
•  M. Esposito, C. Hennersperger, R. Göbl, L. Demaret, M. Storath, N. Navab, M. Baust, A. Weinmann. Total variation regularization of pose signals with an application to 3D freehand ultrasound. IEEE Transactions on Medical Imaging, 38(10):2245–2258, 2019
• L. Kiefer, S. Petra, M. Storath, A. Weinmann. Direct MRI segmentation from k-space data by iterative Potts minimization. SSVM 2019, 406–418

2018

• D. Fortun, M. Storath, D. Rickert, A. Weinmann, M. Unser. Fast piecewise-affine motion estimation without segmentation. IEEE Transactions on Image Processing, 27(11):5612–5624, 2018
• W. Erb, A. Weinmann, M. Ahlborg, C. Brandt, G. Bringout, T. Buzug, J. Frikel, C. Kaethner, T. Knopp, T. März, M. Möddel, M. Storath, A. Weber. Mathematical analysis of the 1D model and reconstruction schemes for magnetic particle imaging. Inverse Problems, 34(5):055012, 2018
• K. Bredies, M. Holler, M. Storath, A. Weinmann. Total generalized variation for manifold-valued data. SIAM Journal on Imaging Sciences, 11(3):1785–1848, 2018
• M. Kiechle, M. Storath, A. Weinmann, M. Kleinsteuber. Model-based learning of local image features for unsupervised texture segmentation. IEEE Transactions on Image Processing, 27(4):1994–2007, 2018
• M. Storath, A. Weinmann. Fast median filtering for phase or orientation data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(3):639–652, 2018
•  A. Weinmann. Variational Methods for the Reconstruction of Signals with Discontinuities. Habilitation thesis, Osnabrück University, 2018

2017

• M. Storath, D. Rickert, M. Unser, A. Weinmann. Fast segmentation from blurred data in 3D fluorescence microscopy. IEEE Transactions on Image Processing, 26(10):4856–4870, 2017
• M. Storath, A. Weinmann, M. Unser. Jump-penalized least absolute values estimation of scalar or circle-valued signals. Information and Inference: A Journal of the IMA, 6(3):225–245, 2017
• M. Storath, C. Brandt, M. Hofmann, T. Knopp, J. Salamon, A. Weber, A. Weinmann. Edge preserving and noise reducing reconstruction for magnetic particle imaging. IEEE Transactions on Medical Imaging, 36(1):74–85, 2017

2016

• T. März, A. Weinmann. Model-based reconstruction for magnetic particle imaging in 2D and 3D. Inverse Problems and Imaging, 10(4):1087–1110, 2016
• A. Stefanoiu, A. Weinmann, M. Storath, N. Navab, M. Baust. Joint segmentation and shape regularization with a generalized forward backward algorithm. IEEE Transactions on Image Processing, 25(7):3384–3394, 2016
• M. Baust, A. Weinmann, M. Wieczorek, T. Lasser, M. Storath, N. Navab. Combined tensor fitting and TV regularization in diffusion tensor imaging based on a Riemannian manifold approach. IEEE Transactions on Medical Imaging, 35(8):1972–1989, 2016
• M. Bačák, R. Bergmann, G. Steidl, A. Weinmann. A second order non-smooth variational model for restoring manifold-valued images. SIAM Journal on Scientific Computing, 38(1):A567–A597, 2016
• M. Storath, A. Weinmann, M. Unser. Exact algorithms for L1-TV regularization of real-valued or circle-valued signals. SIAM Journal on Scientific Computing, 38(1):A614–A630, 2016
• R. Bergmann, A. Weinmann. A second order TV-type approach for inpainting and denoising higher dimensional combined cyclic and vector space data. Journal of Mathematical Imaging and Vision, 55(3):401–427, 2016
• A. Weinmann, L. Demaret, M. Storath. Mumford-Shah and Potts regularization for manifold-valued data. Journal of Mathematical Imaging and Vision, 55(3):428–445, 2016

2015

• K. Hohm, M. Storath, A. Weinmann. An algorithmic framework for Mumford-Shah regularization of inverse problems in imaging. Inverse Problems, 31(11):115011, 2015 (Highlight 2015 of Inverse Problems)
• A. Weinmann, M. Storath. Iterative Potts and Blake-Zisserman minimization for the recovery of functions with discontinuities from indirect measurements. Proceedings of the Royal Society A, 471(2176):20140638, 2015
• A. Weinmann, M. Storath, L. Demaret. The L1-Potts functional for robust jump-sparse reconstruction. SIAM Journal on Numerical Analysis, 53(1):644–673, 2015
• M. Storath, A. Weinmann, J. Frikel, M. Unser. Joint image reconstruction and segmentation using the Potts model. Inverse Problems, 31(2):025003, 2015 (Highlight 2015 of Inverse Problems)
• M. Wieczorek, J. Vogel, A. Weinmann, C. Jud, F. Schaff, M. Storath, F. Pfeiffer et al. Total variation regularization for X-ray tensor tomography. Fully3D 2015
• M. Baust, L. Demaret, M. Storath, N. Navab, A. Weinmann. Total variation regularization of shape signals. CVPR 2015
• R. Bergmann, A. Weinmann. Inpainting of cyclic data using first and second order differences. EMMCVPR 2015, 155–168

2014 and before

• R. Bergmann, F. Laus, G. Steidl, A. Weinmann. Second order differences of cyclic data and applications in variational denoising. SIAM Journal on Imaging Sciences, 7(4):2916–2953, 2014
• A. Weinmann, L. Demaret, M. Storath. Total variation regularization for manifold-valued data. SIAM Journal on Imaging Sciences, 7(4):2226–2257, 2014
• M. Storath, A. Weinmann. Fast partitioning of vector-valued images. SIAM Journal on Imaging Sciences, 7(3):1826–1852, 2014
• M. Storath, A. Weinmann, L. Demaret. Jump-sparse and sparse recovery using Potts functionals. IEEE Transactions on Signal Processing, 62(14):3654–3666, 2014
• M. Storath, A. Weinmann, M. Unser. Unsupervised texture segmentation using monogenic curvelets and the Potts model. ICIP 2014, 4348–4352
• A. Weinmann. Interpolatory multiscale representation for functions between manifolds. SIAM Journal on Mathematical Analysis, 44(1):162–191, 2012
• A. Weinmann. Subdivision schemes with general dilation in the geometric and nonlinear setting. Journal of Approximation Theory, 164(1):105–137, 2012
• J. Wallner, E. Nava Yazdani, A. Weinmann. Convergence and smoothness analysis of subdivision rules in Riemannian and symmetric spaces. Advances in Computational Mathematics, 34(2):201–218, 2011
• A. Weinmann, R. Lasser. Lipschitz spaces with respect to Jacobi translation. Mathematische Nachrichten, 284(17–18):2312–2326, 2011
• A. Weinmann. Nonlinear subdivision schemes on irregular meshes. Constructive Approximation, 31(3):395–415, 2010
• A. Weinmann. Analysis of nonlinear geometric subdivision schemes on polyhedral meshes. PhD thesis, Graz University of Technology, 2010

Open-Source-Software

MPISuperRes-PnP: Super-Resolution-Rekonstruktion für Magnetic Particle Imaging mit einem Zero-Shot-Plug-and-Play-Ansatz (mit V. Gapyak und T. März)

Pottslab: Mehrklassen-Bildsegmentierung für Grau-, Farb- und Mehrkanalbilder mit dem Potts-Modell (mit M. Storath)

CircleMedianFilter: Schneller Medianfilter für kreiswertige Daten wie Phasen- oder Orientierungsbilder (mit M. Storath)

L1TV: Entrauschen und Rekonstruktion stückweise konstanter Signale mit dem L1-TV-Modell (mit M. Storath)

MumfordShah2D: Kantenerhaltende Glättung auf Basis des Mumford-Shah-Modells (mit M. Storath)

PALMS: Parallele Bildzerlegung mit dem stückweise affin-linearen Mumford-Shah-Modell, als Online-Demo (mit L. Kiefer und M. Storath)

Since 2025: Research professorship “Algorithmics in AI”, Technical University of Applied Sciences Würzburg-Schweinfurt (THWS)

2018: Habilitation, Osnabrück University: “Variational Methods for the Reconstruction of Signals with Discontinuities”

2015–2025: Professor of Mathematics and Image Processing, Darmstadt University of Applied Sciences; established the research group Algorithms for Computer Vision, Imaging and Data Analysis

2011–2016: Researcher at Helmholtz Zentrum München and the Technical University of Munich

2010: Doctorate (Dr. rer. nat.), Graz University of Technology: “Analysis of nonlinear geometric subdivision schemes on polyhedral meshes”

2007–2011: University assistant at the Institute of Geometry, Graz University of Technology

2007: Technical Risk Management, Siemens Corporate Technology, Munich

2006: Diploma in Mathematics with a minor in Computer Science, Technical University of Munich

Further information

• Google Scholar
• ORCID