Publications

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Author Title [ Type(Desc)] Year
Journal Article
Diego, F, Reichinnek, S, Both, M and Hamprecht, F A (2013). Automated Identification of Neuronal Activity from Calcium Imaging by Sparse Dictionary Learning. ISBI 2013. Proceedings. 1058-1061PDF icon Technical Report (2.82 MB)
Mikut, R, Dickmeis, T, Driever, W, Geurts, P, Hamprecht, F A, Kausler, B X, Ledesma-Carbayo, M, Marée, R, Mikula, K, Pantazis, P, Ronneberger, O, Santos, A and Stotzka, R (2013). Automated Processing of Zebrafish Imaging Data: A Survey. Zebrafish. 10 (3)PDF icon Technical Report (1.73 MB)
Kreshuk, A, Walecki, R, Köthe, U, Gierthmühlen, M, Plachta, D, Genoud, C, Haastert-Talini, K and Hamprecht, F A (2015). Automated Tracing of Myelinated Axons and Detection of the Nodes of Ranvier in Serial Images of Peripheral Nerves. Journal of Microscopy. 259 (2) 143-154
Zechmann, C M, Menze, B H, Kelm, B Michael, Zamecnik, P, Ikinger, U, Waldherr, R, Delorme, S, Hamprecht, F A and Bachert, P (2012). Automated vs. manual pattern recognition of 3D 1H MRSI data of patients with prostate cancer. Academic Radiology. 19, 6 675-684
Keuchel, J, Naumann, S, Heiler, M and Siegmund, A (2002). Automatic Land Cover Analysis for Tenerife by Supervised Classification using Remotely Sensed Data. Remote Sensing of Environment
Petra, S and Schnörr, C (2014). Average Case Recovery Analysis of Tomographic Compressive Sensing. Linear Algebra and its Applications. 441 168-198PDF icon Technical Report (1.85 MB)
Haußmann, M, Gerwinn, S and Kandemir, M (2019). Bayesian Prior Networks with PAC Training. arXiv preprint arXiv:1906.00816
Hissmann, M and Hamprecht, F A (2005). Bayesian surface estimation for white light interferometry. Optical Engineering. 44 1-9PDF icon Technical Report (549.46 KB)
Kamann, C and Rother, C (2019). Benchmarking the Robustness of Semantic Segmentation Models. http://arxiv.org/abs/1908.05005
Yarlagadda, P and Ommer, B (2015). Beyond the Sum of Parts: Voting with Groups of Dependent Entities. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. 37 1134--1147. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6926849
Hansen, K, Rathke, F, Schroeter, T, Rast, G, Fox, T, Kriegl, J M and Mika, S (2009). Bias-correction of regression models: a case study on hERG inhibition. J. Chem. Inf. Model. 49 1486–1496
Voss, B, Stapf, J, Berthe, A and Garbe, C S (2012). Bichromatic Particle Streak Velocimetry bPSV -- Interfacial, v3C3D velocimetry using a single camera. Exp. Fluids
Fehr, J and Jähne, B (2012). Bilder berechnen - nicht nur aufnehmen. Optik & Photonik. 7 50-53
Fehr, J and Jähne, B (2012). Bilder berechnen --- nicht nur aufnehmen : ``Computational Photography'' wird zunehmend interessant für die industrielle Bildverarbeitung. Optik & Photonik. 7 50--53
Jähne, (1994). Bildverarbeitung für die Meeresforschung. Ruperto Carola. 10--15. http://www.uni-heidelberg.de/uni/presse/rc7/2.html
Keuchel, J, Schnörr, C, Schellewald, C and Cremers, D (2003). Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming. 25 1364–1379
Ozlu, N, Monigatti, F, Renard, B Y, Field, C M, Steen, H, Mitchison, T J and Steen, J J (2009). Binding partner switching on microtubules and aurora-B in the mitosis to cytokinesis transition. Molecular & Cellular Proteomics
Bendinger, A L, Debus, C, Glowa, C, Karger, C P, Peter, J and Storath, M (2019). Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models, in press. Physics in Medicine and Biology. 64
Lempitsky, V, Blake, A and Rother, C (2012). Branch-and-mincut: Global optimization for image segmentation with high-level priors. Journal of Mathematical Imaging and Vision. 44 315–329
Mersmann, S, Seitel, A, Erz, M, Jähne, B, Nickel, F, Mieth, M, Mehrabi, A and Maier-Hein, L (2013). Calibration of time-of-flight cameras for accurate intraoperative surface reconstruction. Med. Phys. 40 082701
Kleesiek, J, Morshuis, J Nikolas, Isensee, F, Deike-Hofmann, K, Paech, D, Kickingereder, P, Köthe, U, Rother, C, Forsting, M, Wick, W, Bendszus, M, Schlemmer, H Peter and Radbruch, A (2019). Can Virtual Contrast Enhancement in Brain MRI Replace Gadolinium?: A Feasibility Study. Investigative Radiology. 54 653–660
Hamprecht, F A, Thiel, W and van Gunsteren, W F (2002). Chemical library subset selection algorithms: a unified derivation using spatial statistics. Journal of Chemical Information and Computer Sciences. 42 414-428
Lenzen, F, Becker, F, Lellmann, J, Petra, S and Schnörr, C (2013). A Class of Quasi-Variational Inequalities for Adaptive Image Denoising and Decomposition. Computational Optimization and Applications (COAP). 54 (2) 371-398
Lenzen, F, Becker, F, Lellmann, J, Petra, S and Schnörr, C (2013). A class of quasi-variational inequalities for adaptive image denoising and decomposition. Computational Optimization and Applications. Springer Netherlands. 54 371-398. http://dx.doi.org/10.1007/s10589-012-9456-0PDF icon Technical Report (748.66 KB)
Geese, M, Jähne, B and Ruhnau, P (2012). CNN Based Dark Signal Non-Uniformity Estimation. CNNA. 1-6
Breitenreicher, D, Lellmann, J and Schnörr, C (2013). COAL: a generic modelling and prototyping framework for convex optimization problems of variational image analysis. Optimization Methods and Software. 28 1081-1094. http://www.tandfonline.com/doi/abs/10.1080/10556788.2012.672571PDF icon Technical Report (1.69 MB)
Jähne, B, Schmidt, M and Rocholz, R (2005). Combined optical slope/height measurements of short wind waves: principles and calibration. Meas. Sci. Technol. 16 1937--1944
Neumann, J, Schnörr, C and Steidl, G (2005). Combined SVM-based Feature Selection and Classification. Machine Learning. 61 129-150
Baust, M, Weinmann, A, Wieczorek, M, Lasser, T, Storath, M and Navab, N (2016). Combined Tensor Fitting and TV Regularization in Diffusion Tensor Imaging based on a Riemannian Manifold Approach. IEEE Transactions on Medical Imaging. 35 1972–1989PDF icon Technical Report (8.65 MB)
Nagel, L, Krall, K Ellen and Jähne, B (2015). Comparative heat and gas exchange measurements in the Heidelberg Aeolotron, a large annular wind-wave tank. Ocean Sci. 11 111--120
Nagel, L, Krall, K Ellen and Jähne, B (2014). Comparative heat and gas exchange measurements in the Heidelberg Aeolotron, a large annular wind-wave tank. Ocean Sci. Discuss. 11 1691--1718
Szeliski, R, Zabih, R, Scharstein, D, Veksler, O, Kolmogorov, V, Agarwala, A, Tappen, M and Rother, C (2008). A comparative study of energy minimization methods for Markov random fields with smoothness-based priors. IEEE Transactions on Pattern Analysis and Machine Intelligence. Springer-Verlag. 30 1068–1080. http://vision.middlebury.edu/MRF.
Szeliski, R, Zabih, R, Scharstein, D, Veksler, O, Kolmogorov, V, Agarwala, A, Tappen, M and Rother, C (2008). A comparative study of energy minimization methods for Markov random fields with smoothness-based priors. IEEE Transactions on Pattern Analysis and Machine Intelligence. 30 1068–1080
Kappes, J H, Andres, B, Hamprecht, F A, Schnörr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kröger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. International Journal of Computer Vision. 115 155–184. http://hci.iwr.uni-heidelberg.de/opengm2/
Kappes, J H, Andres, B, Hamprecht, F A, Schnörr, C, Nowozin, S, Batra, D, Kim, S, Kausler, B X, Kröger, T, Lellmann, J, Komodakis, N, Savchynskyy, B and Rother, C (2015). A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems. International Journal of Computer Vision. 115 155–184

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