Biblio

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[ Author(Desc)] Title Type Year
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P
Peters, J., & Umlauf G. (2001).  Computing curvature bounds for bounded curvature subdivision. Computer Aided Geometric Design. 18, 455-462.PDF icon CurvatBnd.pdf (179.48 KB)
Prautzsch, H., & Umlauf G. (1998).  A G^2 subdivision algorithm. Computing. 13, 217-224.PDF icon g2algorithm.pdf (196.14 KB)
Prautzsch, H., & Umlauf G. (1999).  Triangular G^2 splines. (Laurent, P.-L., Sablonniere P., & Schumaker L.L., Ed.).Curve and Surface Design. PDF icon TriG2Splines.pdf (393.87 KB)
Prautzsch, H., & Umlauf G. (2000).  A G^1 and a G^2 subdivision scheme for trinagular nets. International Journal on Shape Modelling. 6, 21-35.PDF icon G1G2TriAlgo.pdf (2.61 MB)
Prautzsch, H., & Umlauf G. (2006).  Parametrizations for triangular G^k spline surfaces of low degree. ACM Transactions on Graphics. 24, 1281-1293.PDF icon GkSplineSurf.pdf (539.25 KB)
Prautzsch, H., & Umlauf G. (1999).  Improved triangular subdivision schemes. (Wolter, F.-E., & Patrikalakis N.M., Ed.).Proceedings of the CGI '98. PDF icon TriSub.pdf (1.73 MB)
R
Rohrbach, J., Rainhard T., Sick B., & Dürr O. (2019).  Bone erosion scoring for rheumatoid arthritis with deep convolutional neural networks.
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Schall, M., Grunwald M., Umlauf G., & Franz M. O. (2015).  Radiometric calibration of digital cameras using Gaussian processes. SPIE Optics+ Optoelectronics. PDF icon Schall et al_2015_Radiometric calibration of digital cameras using Gaussian processes.PDF (953.2 KB)
Schall, M., Buehrig H. P., Schambach M-P., & Franz M. O. (2018).  LSTM Networks for Edit Distance Calculation with Exchangeable Dictionaries. 13th IAPR International Workshop on Document Analysis Systems. PDF icon 2018-04 LSTM Networks for Edit Distance Calculation with Exchangeable Dictionaries.pdf (145.78 KB)
Schall, M., Schambach M-P., & Franz M. O. (2018).  Multi-Dimensional Connectionist Classification: Reading Text in One Step. 13th IAPR International Workshop on Document Analysis Systems. PDF icon 2018-04 Multi-Dimensional Connectionist Classification Reading Text in One Step.pdf (485.57 KB)
Schall, M., Sacha D., Stein M., Franz M. O., & Keim D. A. (2018).  Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition. Visualization in Data Science (VDS at IEEE VIS) 2018. PDF icon Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition.pdf (1.03 MB)
Schall, M., Schambach M-P., & Franz M. O. (2016).  Increasing robustness of handwriting recognition using character n-gram decoding on large lexica. 12th IAPR International Workshop on Document Analysis Systems. PDF icon Schall et al_2016_Increasing robustness of handwriting recognition using character n-gram decoding on large lexica.pdf (440.82 KB)
Schall, M., Schambach M-P., & Franz M. O. (2019).  Dissecting Multi-Line Handwriting for Multi-Dimensional Connectionist Classification. 15th IAPR International Conference on Document Analysis and Recognition. PDF icon Dissecting Multi-Line Handwriting for Multi-Dimensional Connectionist Classification.pdf (553.24 KB)
Schall, M., Schambach M-P., & Franz M. O. (2016).  Improving gradient-based LSTM training for offline handwriting recognition by careful selection of the optimization method. Conference: BW-CAR Symposium on Information and Communication Systems (SInCom). PDF icon 2016-12 Improving gradient-based LSTM training for offline handwriting recognition by careful selection of the optimization method.pdf (803.54 KB)
Schambach, M-P., von der Nüll S., & Schall M. (2019).  Fast and Reliable Acquisition of Truth Data for Document Analysis using Cyclic Suggest Algorithms. ICDAR-OST: The 2nd International Workshop on Open Services and Tools for Document Analysis. PDF icon Fast and Reliable Acquisition of Truth Data for Document Analysis using Cyclic Suggest Algorithms.pdf (776.45 KB)
Scharpf, P., Hong C. Lap, & Duerr O. (2021).  Accelerating Active Learning Image Labeling Through Bulk Shift Recommendations. 2021 International Conference on Data Mining Workshops (ICDMW). 398-404.
Scharpf, P., Hong C. Lap, & Dürr O. (2021).  Accelerating Active Learning Image Labeling Through Bulk Shift Recommendations. 2021 International Conference on Data Mining Workshops (ICDMW). 398–404.
Schuldt, T., Schubert C., Krutzik M., Bote L., Gaaloul N., Hartwig J., et al. (2015).  Design of a dual species atom interferometer for space. Experimental Astronomy. 39, 167-206.PDF icon Schuldt et al._2015_Design of a dual species atom interferometer for space.pdf (2.98 MB)
Schuldt, T., Döringshoff K., Stühler J., Kovalchuk E., Franz M. O., Gohlke M., et al. (2013).  A compact high-performance frequency reference for space applications. {29th Intl. Symposium on Space Technology and Science (ISTS 2013), Nagoya (Japan)}. PDF icon Schuldt et al._2013_A Compact High-Performance Frequency Reference for Space Applications.pdf (369.85 KB)
Schwamberger, V., & Franz M. O. (2010).  Simple algorithmic modifications for improving blind steganalysis performance. {Proc. of the 2010 Workshop on Multimedia and Security (MM&Sec 2010)}. PDF icon Schwamberger, Franz_2010_Simple Algorithmic Modifications for Improving Blind Steganalysis Performance.pdf (813.87 KB)
Schwamberger, V., Le P. H. D., Schölkopf B., & Franz M. O. (2010).  The influence of the image basis on modeling and steganalysis performance. (Böhme, R., Fong P.W.L., & Safavi-Naini R., Ed.).{Proc. 12th Intl. Conf. on Information Hiding (IH-2010)}. 133–144.PDF icon Schwamberger et al._2010_The Influence of the Image Basis on Modeling and Steganalysis Performance.pdf (392.83 KB)
Seepold, R., Dermati C., Kostka A., Pfeil L., Lange R., Hermann M., et al. (2016).  Analyzing environmental conditions and vital signs to increase healthy living. Mobile Networks for Biometric Data Analysis.
Sick, B., Hothorn T., & Dürr O. (2021).  Deep transformation models: Tackling complex regression problems with neural network based transformation models. Accepted for Proceedings of the 25th International Conference on Pattern Recognition (ICPR), Milan/Online, 2021.
Siegismund, D., Tolkachev V., Heyse S., Sick B., Dürr O., & Steigele S. (2018).  Developing deep learning applications for life science and pharma industry. Drug research. 68, 305–310.
Sinz, F., & Franz M. O. (2004).  Learning depth. (Bülthoff, H. H., Mallot H. A., Ulrich R., & Wichmann F. A., Ed.).{Proc. 7. Tübinger Wahrnehmungskonferenz (TWK 2004)}. 68.PDF icon Sinz et al Learning depth 2004.pdf (197 KB)

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