Export 1514 results:
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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
Waas, S and Jähne, B (1996). Combined height/slope/curvature measurements of short ocean wind waves. Proc.\ The Air-Sea Interface, Radio and Acoustic Sensing, Turbulence and Wave Dynamics, Marseille, 24--30. June 1993. RSMAS, University of Miami. 383--388
Waas, S and Jähne, B (1994). Combined height/slope/curvature measurements of short ocean wind waves
Carlsohn, M F, Menze, B H, Kelm, B M, Hamprecht, F A, Kercek, A, Leitner, R and Polder, G (2006). Color image processing. CRC Press. 7(17) 393-419
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. icon Technical Report (1.69 MB)
Geese, M, Ruhnau, P and Jähne, B (2012). CNN based dark signal non-uniformity estimation. Cellular Nanoscale Networks and Their Applications (CNNA), 2012 13th International Workshop on. 1--6
Geese, M, Jähne, B and Ruhnau, P (2012). CNN Based Dark Signal Non-Uniformity Estimation. CNNA. 1-6
Brosowsky, M (2017). Cluster Resolving For Animal Tracking: Multi Hypotheses Tracking With Part Based Model For Object Hypotheses Generation And Pose Estimation. University of Heidelberg
Wenig, M, Leue, C, Platt, U, Jähne, B and Haußecker, H (2000). Cloud classification analyzing image sequences. Computer Vision and Applications. A Guide for Students and Practitioners. Academic Press. 652--653
Long, S R and Klinke, J (2002). A closer look at short waves generated by wave interactions with adverse currents. Gas Transfer at Water Surfaces. American Geophysical Union. 127 121--128
Bautista, M, Sanakoyeu, A, Sutter, E and Ommer, B (2016). CliqueCNN: Deep Unsupervised Exemplar Learning. Proceedings of the Conference on Advances in Neural Information Processing Systems (NIPS). MIT Press, Barcelona. icon Article (5.79 MB)
Kaster, F O, Kelm, B M, Zechmann, C M, Weber, M - A, Hamprecht, F A and Nix, O (2009). Classification of Spectroscopic Images in the DIROlab Environment. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany. Springer. 25/V 252--255PDF icon Technical Report (145.73 KB)
Menze, B H and Ur, J A (2007). Classification of multispectral ASTER imagery in the archaeological survey for settlement sites of the Near East. Proc 10th International Symposium on Physical Measurements and Signature in Remote Sensing (ISPMRS 07), Davos, Switzerland. International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesPDF icon Technical Report (920.71 KB)
Menze, B H, Wormit, M, Bachert, P, Lichy, M P, Schlemmer, H - P and Hamprecht, F A (2004). Classification of in vivo magnetic resonance spectra. Classification in ubiquitous challenge: Proceedings of the GfKl 2004. Springer. 362-369PDF icon Technical Report (240.1 KB)
Hamprecht, F A (2004). Classification. Practical Handbook on Image Processing for Scientific and Technical Applications. CRC Press. 509-519PDF icon Technical Report (320.84 KB)
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. icon Technical Report (748.66 KB)
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
Heers, J, Schnörr, C and Stiehl, H S (1998). A class of parallel algorithms for nonlinear variational image segmentation. Proc.~Noblesse Workshop on Non--Linear Model Based Image Analysis (NMBIA'98)
Kelm, B M, Menze, B H, Neff, T, Zechmann, C M and Hamprecht, F A (2006). CLARET: a tool for fully automated evaluation of MRSI with pattern recognition methods.. Bildverarbeitung für die Medizin 2006 - Algorithmen, Systeme, Anwendungen. Springer. 51-55. icon Technical Report (275.25 KB)
Schmund, D, Münsterer, T, Lauer, H, Jähne, B and Jähne, B (1995). The circular wind wave facilities at the University of Heidelberg. Air-Water Gas Transfer - Selected papers from the Third International Symposium on Air-Water Gas Transfer. AEON. 505--516
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
Erz, M (2011). Charakterisierung von Laufzeitkamerasystemen für Lumineszenzlebensdauermessungen. IWR, Fakultät für Physik und Astronomie, University of Heidelberg.
Wolf, S (2016). Cell Tracking With Graphical Model Using Higher Order Features On Track Segments. University of Heidelberg
Kandemir, M and Hamprecht, F A (2015). Cell event detection in phase-contrast microscopy sequences from few annotations. MICCAI. Proceedings. Springer. LNCS 9351 316-323PDF icon Technical Report (564.69 KB)
Zhang, C, Yarkony, J and Hamprecht, F A (2014). Cell detection and segmentation using correlation clustering. MICCAI. Proceedings. Springer. 9-16PDF icon Technical Report (8.06 MB)
Welbl, J (2014). Casting Random Forests as Artificial Neural Networks (and Profiting from It). GCPR. Proceedings. 765-771PDF icon Technical Report (376.24 KB)
Straehle, C N, Köthe, U, Knott, G and Hamprecht, F A (2011). Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images. MICCAI 2011, Proceedings. Springer. 6891 653-660PDF icon Technical Report (1.69 MB)
Maier-Hein, L, Mersmann, S, Kondermann, D, Bodenstedt, S, Sanchez, A, Stock, C, Kenngott, H, Eisenmann, M and Speidel, S (2014). Can masses of non-experts train highly accurate image classifiers? A crowdsourcing approach to instrument segmentation in laparoscopic images. MICCAI
Zechmann, C, Kelm, B M, Zamecnik, P, Ikinger, U, Waldherr, R, Röll, S, Delorme, S, Hamprecht, F A and Bachert, P (2006). Can man still beat the machine? Automated vs. manual pattern recognition of 3D MRSI data of prostate cancer patients. Proceedings of the 16th ISMRMPDF icon Technical Report (664.38 KB)
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
Rocholz, R (2010). Calibration Of The 2010-Cisg Setup At The Aeolotron. Institute of Environmental Physics, University of Heidelberg
Jähne, B and Schultz, H (1992). Calibration and accuracy of optical slope measurements for short wind waves. Optics of the Air-Sea Interface: Theory and Measurements. 1749 222--233