Biblio

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Author [ Title(Desc)] Type Year
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E
Yovel, Y., Franz M. O., Stilz P., & Schnitzler H.-U. (2011).  Echo-based object recognition in echolocating bats. J. Comp. Phyiol. A. 197, 475–490.
Dürr, O., Dieterich W., Maas P., & Nitzan A. (2002).  Effective medium theory of conduction in stretched polymer electrolytes. arXiv preprint cond-mat/0202165.
Kienzle, W., Bakır G. H., & Franz M. O. (2004).  Efficient approximations for support vector machines for object detection. (Rasmussen, C. E., Bülthoff H. H., & Giese M. A., Ed.).{Pattern Recognition, Proc. of the 26th DAGM Symposium}. 54–61.PDF icon Kienzle, Bakır, Franz_2004_Efficient approximations for support vector machines for object detection.pdf (165.13 KB)
Middendorf, L., Mühlbauer F., Umlauf G., & Bobda C. (2007).  Embedded vertex shader in FPGA. (A. al., R. et, Ed.).Embedded System Design: Topics, Techniques and Trends.
Laube, P., Franz M. O., & Umlauf G. (2017).  Evaluation of features for SVM-based classification of geometric primitives in point clouds. Machine Vision Applications (MVA), 2017 Fifteenth IAPR International Conference on. 59–62.PDF icon paper.pdf (1.5 MB)
Bohnet, D., & Vartziotis D. (2016).  Existence of an attractor for a geometric tetrahedron transformation. Differential Geom. Appl.. 49,
Hoher, P., Reuter J., Dold D., Griesser D., Govaers F., & Koch W. (2023).  Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Gaussian Processes Regression Model. International Conference on Information Fusion (FUSION). 1-8.
Dahmen, H.-J., Franz M. O., & Krapp H. G. (2001).  Extracting egomotion from optic flow: limits of accuracy and neural matched filters. (Zanker, J. M., & Zeil J., Ed.).{Motion Vision: Computational, Neural and Ecological Constraints}. 143-168.PDF icon Dahmen, Franz, Krapp_2001_Extracting egomotion from optic flow- limits of accuracy and neural matched filters.pdf (223.04 KB)
F
Kienzle, W., Bakır G. H., Franz M. O., & Schölkopf B. (2005).  Face detection – efficient and rank deficient. (Saul, L. K., Weiss Y., & Bottou L., Ed.).{Advances in Neural Information Processing Systems 17}. 673–680.PDF icon Kienzle et al._2005_Face Detection --- Efficient and Rank Deficient.pdf (145.73 KB)
Hermann, M., Umlauf G., Goldlücke B., & Franz M. O. (2022).  Fast and efficient image novelty detection based on mean-shifts. Sensors | Unusual Behavior Detection Based on Machine Learning .
Hermann, M., Umlauf G., & Franz M. O. (2022).  Fast and memory-efficient independent component analysis using Lie group techniques. International Conference on Curves and Surfaces.
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)
Burkhart, D., Hamann B., & Umlauf G. (2011).  Finite element analysis for linear elastic solids based on subdivision schemes. Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop. PDF icon FEALinearElasticSolids.pdf (2.35 MB)
Axthelm, R. (2016).  Finite Element Simulation of a Macroscopic Model for Pedestrian Flow. Traffic and Granular Flow. 10.1007/978-3-319-33482-0_30, 233–240.
Bohnet, D., & Vartziotis D. (2018).  Fractal Curves from Prime Trigonometric Series. Fractal Fract.. 2(2), 

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