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Journal Article

K. Rohr and Schnörr, C., “An Efficient Approach to the Identification of Characteristic Intensity Variations”, vol. 11, pp. 273–277, 1993.

J. Funke, Andres, B., Hamprecht, F. A., Cardona, A., and Cook, M., “Efficient Automatic 3D-Reconstruction of Branching Neurons from EM Data”, CVPR 2012. Proceedings, pp. 1004-1011, 2012.

Technical Report (1.64 MB)

A. Criminisi, Shotton, J., Blake, A., and Torr, P., “Efficient dense stereo and novel-view synthesis for gaze manipulation in one-to-one teleconferencing”, 2004.

A. Criminisi, Blake, A., Rother, C., Shotton, J., and Torr, P. H. S., “Efficient dense stereo with occlusions for new view-synthesis by four-state dynamic programming”, International Journal of Computer Vision, vol. 71, pp. 89–110, 2007.

B. Savchynskyy, Schmidt, S., Kappes, J. H., and Schnörr, C., “Efficient MRF Energy Minimization via Adaptive Diminishing Smoothing”, UAI. Proceedings, pp. 746-755, 2012.

J. Neumann, Schnörr, C., and Steidl, G., “Efficient Wavelet Adaption for Hybrid Wavelet-Large Margin Classifiers”, Pattern Recognition, vol. 38, pp. 1815-1830, 2005.

P. Libner, Jähne, B., and Plate, E. J., “Ein neue Methode zur lokalen und momentanen Bestimmung der Wiederbelüftungsraten von Gewässern”, Wasserwirtschaft, vol. 77, p. 230--235, 1987.

M. P. Lichy, Bachert, P., Hamprecht, F. A., Weber, M. - A., Debus, J., Schulz-Ertner, D., Kauczor, H. - U., and Schlemmer, H. - P., “Einsatz der 1H-MR-spektroskopischen Bildgebung in der Strahlentherapie: Cholin als Marker für die Bestimmung der relativen Wahrscheinlichkeit eines Tumorprogresses nach Bestrahlung glialer Hirntumoren”, Zeitung für Röntgenforschung, vol. 178, pp. 627-633, 2006.

B. Jähne, “EMVA 1288 standard for machine vision -- objective specification of vital camera data”, Optik & Photonik, vol. 5, p. 53--54, 2010.

T. M. Hehn, Kooij, J. F. P., and Hamprecht, F. A., “End-to-End Learning of Decision Trees and Forests”, International Journal of Computer Vision, vol. 128, pp. 997-1011, 2020.

B. Andres, Kondermann, C., Kondermann, D., Köthe, U., Hamprecht, F. A., and Garbe, C. S., “On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation”, Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, pp. 1-6, 2008.

Technical Report (1.58 MB)

B. Michael Kelm, Menze, B. H., Nix, O., Zechmann, C. M., and Hamprecht, F. A., “Estimating Kinetic Parameter Maps from Dynamic Contrast-Enhanced MRI using Spatial Prior Knowledge”, IEEE Transaction on Medical Imaging, vol. 28:10, pp. 1534-1547, 2009.

Technical Report (419.8 KB)

B. Y. Renard, Timm, W., Kirchner, M., Steen, J. A. J., Hamprecht, F. A., and Steen, H., “Estimating the Confidence of Peptide Identifications without Decoy Databases”, Analytical Chemistry, pp. 4314-4318, 2010.

Technical Report (619.11 KB)

C. S. Garbe, Spies, H., and Jähne, B., “Estimation of complex motion from thermographic image sequences”, SPIE Proc., vol. 5073, p. 303--317, 2003.

C. S. Garbe, Spies, H., and Jähne, B., “Estimation of surface flow and net heat flux from infrared image sequences”, Journal of Mathematical Imaging and Vision, vol. 19, p. 159--174, 2003.

C. Schellewald, Roth, S., and Schnörr, C., “Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views”, Image Vision Comp., vol. 25, pp. 1301–1314, 2007.

C. Schellewald, Roth, S., and Schnörr, C., “Evaluation of a convex relaxation to a quadratic assignment matching approach for relational object views”, Image Vision Comp., vol. 25, p. 1301--1314, 2007.

Technical Report (439.9 KB)

L. Ardizzone, Mackowiak, R., Rother, C., and Köthe, U., “Exact Information Bottleneck with Invertible Neural Networks: Getting the Best of Discriminative and Generative Modeling”, 2020.

PDF (2.87 MB)

A. Imle, Kumberger, P., Schnellbächer, N. D., Fehr, J., Carillo-Bustamente, P., Ales, J., Schmidt, P., Ritter, C., Godinez, W. J., Müller, B., Rohr, K., Hamprecht, F. A., Schwarz, U. S., Graw, F., and Fackler, O. T., “Experimental and computational analyses reveal that environmental restrictions shape HIV-1 spread in 3D cultures”, Nature Communications, vol. 13;10(1), 2019.

D. M. Kirchhöfer, Holst, G. A., Wouters, F. S., Hock, S., and Jähne, B., “Extended noise equalisation for image compression in microscopical applications”, tm - Technisches Messen, vol. 86, pp. 422–432, 2019.

A. Hosni, Rhemann, C., Bleyer, M., Rother, C., and Gelautz, M., “Fast cost-volume filtering for visual correspondence and beyond”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 35, pp. 504–511, 2013.

M. Storath and Weinmann, A., “Fast median filtering for phase or orientation data”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 3, pp. 639–652, 2018.

Technical Report (7.32 MB)

F. Rathke and Schnörr, C., “Fast Multivariate Log-Concave Density Estimation”, preprint: ArXiv, 2018.

Technical Report (3.54 MB)

F. Rathke and Schnörr, C., “Fast Multivariate Log-Concave Density Estimation”, Comp. Statistics & Data Analysis, vol. 140, pp. 41-58, 2019.

F. Rathke and Schnörr, C., “Fast Multivariate Log-Concave Density Estimation”, Comp. Statistics & Data Analysis, vol. 140, pp. 41–58, 2019.

F. Rathke and Schnörr, C., “Fast Multivariate Log-Concave Density Estimation”, preprint: arXiv, 2018.

J. Weickert, Heers, J., Schnörr, C., Zuiderveld, K. –J., Scherzer, O., and Stiehl, H. –S., “Fast parallel algorithms for a broad class of nonlinear variational diffusion approaches”, Real–Time Imaging, vol. 7, pp. 31–45, 2001.

D. Fortun, Storath, M., Rickert, D., Weinmann, A., and Unser, M., “Fast Piecewise-Affine Motion Estimation Without Segmentation”, IEEE Transactions on Image Processing, vol. 27 , no. 11, pp. 5612 - 5624, 2018.

M. Storath, Rickert, D., Unser, M., and Weinmann, A., “Fast segmentation from blurred data in 3D fluorescence microscopy”, IEEE Transactions on Image Processing, vol. 26, no. 10, 2017.

F. A. Hamprecht, Achleitner, U., Krismer, A. C., Lindner, K. H., Wenzel, V., Strohmenger, H. - U., Thiel, W., and van Gunsteren, W. F., “Fibrillation power: An alternative method of ECG spectral analysis for prediction of countershock success in a porcine model of ventricular fibrillation”, Resuscitation, vol. 50, pp. 287-296, 2001.

K. Ellen Krall and Jähne, B., “First air-sea gas exchange laboratory study at hurricane wind speeds”, Ocean Sci. Discuss., vol. 10, p. 1971--1996, 2013.

K. Ellen Krall and Jähne, B., “First laboratory study of air-sea gas exchange at hurricane wind speeds”, Ocean Sci., vol. 10, p. 257--265, 2014.

C. Thieke, Nix, O., Koehn, A., Floca, R., van Straaten, D., Hahn, H., Strauss, L. G., Siems, U., Graf, M., Pruem, H., Klein, J., Laue, H., and Kaster, F. O., “A framework and multi-application prototype for integrated radiological diagnostics and radiation therapy”, Strahlentherapie und Onkologie, vol. 185, p. 81, 2009.

K. Börner, Hermle, J., Sommer, C., Brown, N. P., Knapp, B., Glass, B., Torralba, G., Reymann, J., Beil, N., Beneke, J., Pepperkok, R., Schneider, R., and Ludwig, T., “From experimental setup to bioinformatics: An RNAi screening platform to identify host factors involved in HIV-1 replication”, Biotechnology Journal, vol. 5, pp. 39-49, 2010.

Technical Report (556.09 KB)

C. Schnörr, “On Functionals with Greyvalue-Controlled Smoothness Terms for Determining Optical Flow”, pami, vol. 15, pp. 1074–1079, 1993.

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