Biblio

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A
Axthelm, R. (2022).  Mathematik mit digitalen Bildern sichtbar machen. Seamless Learning, Grenz- und kontextübergreifendes Lehren und Lernen in der Bodenseeregion. 133-145.
B
Bakır, G. H., Gretton A., Franz M. O., & Schölkopf B. (2004).  Multivariate Regression via Stiefel Manifold Constraints. (Rasmussen, C. E., Bülthoff H. H., Giese M. A., & Schölkopf B., Ed.).{Pattern Recognition, Proc. of the 26th DAGM Symposium (DAGM 2004)}. 262-269.
C
Cieliebak, M., Dürr O., & Uzdilli F. (2014).  Meta-Classifiers Easily Improve Commercial Sentiment Detection Tools.. Language Resources and Evaluation Conference (LREC). 3100–3104.
D
Dürr, O. (1998).  Monte-carlo-simulationen zu polymeren ionenleitern.
Dürr, O., Pendzig P., Dieterich W., & Nitzan A. (2001).  Model studies of diffusion in glassy and polymer ion conductors. arXiv preprint cond-mat/0106196.
F
Franz, M. O. (1998).  Minimalistic visual navigation. Fortschr.-Ber. VDI Reihe 8.
O
Oliver, D., Frisch H., & Dieterich W. (2001).  Melt viscosities of lattice polymers using a Kramers potential treatment. J. Chem. Phys.. 115, 9042–9045.
S
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)
T
Thießen, L., Laube P., Franz M. O., & Umlauf G. (2014).  Merging multiple 3d face reconstructions. (Benyoucef, D., & Reich C., Ed.).Symposium on Information and Communication Systems. 7-12.PDF icon Merging3DFaceReconst.pdf (12.91 MB)