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R. Bremeyer, “Lokale Orientierung zur Auswertung von Streakbildern”, Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ. Heidelberg, 1995.

V. Lempitsky, Rother, C., and Blake, A., “LogCut - Efficient graph cut optimization for markov random fields”, in Proceedings of the IEEE International Conference on Computer Vision, 2007.

U. Schimpf, Nagel, L., and Jähne, B., “Lock-in thermography at the ocean surface: a local and fast method to investigate heat and gas exchange between ocean and atmosphere”, in DPG Frühjahrstagung Dresden, Fachverband Umweltphysik, 2011.

F. Rathke, Desana, M., and Schnörr, C., “Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans”, MICCAI. Proceedings. pp. 177-184, 2017.

Technical Report (4.79 MB)

F. Rathke, Desana, M., and Schnörr, C., “Locally Adaptive Probabilistic Models for Global Segmentation of Pathological OCT Scans”, in Proc. MICCAI, 2017.

W. Li, Hosseini Jafari, O., and Rother, C., “Localizing Common Objects Using Common Component Activation Map”, 2019.

A. Haja, Jähne, B., and Abraham, S., “Localization accuracy of region detectors”, in Proceedings CVPR'08, 2008.

B. Jähne, Jähne, B., and Haußecker, H., “Local structure”, Handbook of Computer Vision and Applications. Volume II: Signal Processing and Pattern Recognition. Academic Press, p. 209--238, 1999.

E. Bodnariuc, Petra, S., Schnörr, C., and Voorneveld, J., “A Local Spatio-Temporal Approach to Plane Wave Ultrasound Particle Image Velocimetry”, in Proc. GCPR, 2017.

J. Fehr, “Local Rotation Invariant Patch Descriptors for 3D Vector Fields”, Pattern Recognition, International Conference on, Istanbul, Turkey, August 23-26, 2010, pp. 1381-1384, 2010.

J. Fehr and Burkhardt, H., “Local Rotation Invariant Patch Descriptors for 3D Vector Fields”, in to be submitted, 2009.

H. Spies, Dierig, T., Garbe, C. S., and Würtz, R. P., “Local models for dynamic processes in image sequences”, in Dynamic Perception, 2002, p. 59--64.

B. Jähne, Jähne, B., and Haußecker, H., “Local averaging”, Handbook of Computer Vision and Applications. Volume II: Signal Processing and Pattern Recognition. Academic Press, p. 153--174, 1999.

S. Weber, Schnörr, C., and Hornegger, J., “A Linear Programming Relaxation for Binary Tomography with Smoothness Priors”, in Proc. Int. Workshop on Combinatorial Image Analysis (IWCIA'03), Palermo, Italy, 2003.

S. Weber, Schüle, T., Schnörr, C., and Hornegger, J., “A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections”, Methods of Information in Medicine, vol. 43, pp. 320–326, 2004.

S. Weber, Schüle, T., Schnörr, C., and Hornegger, J., “A Linear Programming Approach to Limited Angle 3D Reconstruction from DSA Projections”, in Bildverarbeitung für die Medizin 2003, 2003, pp. 41–45.

C. Rother, “Linear multi-view reconstruction of points, lines, planes and cameras using a reference plane”, in Proceedings of the IEEE International Conference on Computer Vision, 2003, vol. 2, pp. 1210–1217.

C. Rother, “Linear Multi-View Reconstruction for Translating Cameras”, Nada.Kth.Se, 2003.

C. Rother and Carlsson, S., “Linear multi view reconstruction with missing data”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2002, vol. 2351, pp. 209–324.

C. Rother and Carlsson, S., “Linear multi view reconstruction and camera recovery using a reference plane”, International Journal of Computer Vision, vol. 49, pp. 117–141, 2002.

C. Rother and Carlsson, S., “Linear multi view reconstruction and camera recovery”, in Proceedings of the IEEE International Conference on Computer Vision, 2001, vol. 1, pp. 42–49.

H. Scharr and Küsters, R., “A linear model for simultaneous estimation of 3D motion and depth”, in Proceedins of IEEE Workshop on Motion and Video Computing 2002, Orlando, 2002.

W. Peckar, Schnörr, C., Rohr, K., Stiehl, H. –S., and Spetzger, U., “Linear and Incremental Estimation of Elastic Deformations in Medical Registration Using Prescribed Displacements”, Machine Graphics & Vision, vol. 7, pp. 807–829, 1998.

M. Diebold, “Light-Field Imaging and Heterogeneous Light Fields”, vol. Dissertation. IWR, Univ. Heidelberg, 2016.

M. Diebold, Blum, O., Gutsche, M., Wanner, S., Garbe, C., Baker, H., and Jähne, B., “Light-field camera design for high-accuracy depth estimation”, in Videometrics, Range Imaging, and Applications XIII, 2015.

M. Diebold, Blum, O., Gutsche, M., Wanner, S., Garbe, C. S., Baker, H., and Jähne, B., “Light-field camera design for high-accuracy depth estimation”, Videometrics, Range Imaging, and Applications XIII. 2015.

B. Krolla, Diebold, M., and Stricker, D., “Light Field from Smartphone-Based Dual Video”, in Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II, Cham: Springer International Publishing, 2015, pp. 600–610.

T. Münsterer and Jähne, B., “A LIF technique for the measurement of concentration profiles in the aqueous mass boundary layer”, in Proc.\ 7th Intern.\ Symp.\ on Appl.\ of Laser Techn.\ to Fluid Mechanics, Lisbon, Portugal, July 11.--14. 1994, 1994, vol. II, p. 29.4.1--5.

T. Münsterer and Jähne, B., “LIF measurements of concentration profiles in the aqueous mass boundary layer”, Exp. Fluids, vol. 25, p. 190--196, 1998.

T. Münsterer, “LIF Investigation of the Mechanisms Controlling Air--Water Mass Transfer at a Free Interface”. Institut für Umweltphysik, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1996.

B. Antic, Milbich, T., and Ommer, B., “Less is More: Video Trimming for Action Recognition”, in Proceedings of the IEEE International Conference on Computer Vision, Workshop on Understanding Human Activities: Context and Interaction, 2013, p. 515--521.

Technical Report (984.89 KB)

E. Kirschbaum, Haußmann, M., Wolf, S., Sonntag, H., Schneider, J., Elzoheiry, S., Kann, O., Durstewitz, D., and Hamprecht, F. A., “LeMoNADe: Learned Motif and Neuronal Assembly Detection in calcium imaging videos”, ICLR. Proceedings. 2019.

T. Kröger, “Learning-based Segmentation for Connectomics”. University of Heidelberg, 2014.

C. Sommer, Fiaschi, L., Hamprecht, F. A., and Gerlich, D., “Learning-based Mitotic Cell Detection in Histopathological Images”, ICPR 2012. Proceedings, pp. 2306-2309, 2012.

Technical Report (1.96 MB)

M. Bautista, Fuchs, P., and Ommer, B., “Learning Where to Drive by Watching Others”, Proceedings of the German Conference Pattern Recognition, vol. 1. Springer-Verlag, Basel, 2017.

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